{"count":422,"next_page":"https://support.lexisnexisip.com/api/v2/help_center/en-us/articles.json?page=2&per_page=30","page":1,"page_count":15,"per_page":30,"previous_page":null,"articles":[{"id":53324168264851,"url":"https://lnip.zendesk.com/api/v2/help_center/en-us/articles/53324168264851.json","html_url":"https://support.lexisnexisip.com/hc/en-us/articles/53324168264851-New-Technology-Package-DRAM-Memory","author_id":26222564335507,"comments_disabled":false,"draft":false,"promoted":false,"position":0,"vote_sum":0,"vote_count":0,"section_id":40390434524051,"created_at":"2026-07-09T14:33:26Z","updated_at":"2026-08-26T11:19:03Z","name":"New Technology Package: DRAM Memory","title":"New Technology Package: DRAM Memory","source_locale":"en-us","locale":"en-us","outdated":false,"outdated_locales":[],"edited_at":"2026-08-26T11:19:03Z","user_segment_id":null,"permission_group_id":20301510583827,"content_tag_ids":[],"label_names":[],"body":"
We're excited to announce the launch of a brand-new technology package in IPlytics: the Memory technology package. This package brings the same curated, pre-built patent landscape approach IPlytics customers already rely on for standards like Wi-Fi 6, 5G, and HEVC, now applied to the technologies powering modern memory and semiconductor systems.
The new package covers patent landscapes across four major DRAM memory standards (Dynamic Random-Access Memory): HBM, GDDR, LPDDR, and DDR. These standards were developed within the Joint Electron Device Engineering Council (JEDEC) standards ecosystem.
Instead of building a search from scratch, users can now go straight to a structured, ready-to-use view of who holds relevant patents, how large each landscape is, and where competitive activity is concentrated.
Unlike other technology packages, the Memory package is built using IPlytics' LLM-based Essentiality Score methodology, which produces an essentiality score (1–100%) and confidence rating for each patent rather than a declared/undeclared classification.
What's New?
Four Memory Landscapes, One Package
The Memory technology package organizes patent data into four distinct technology landscapes, each mapped to a specific memory standard:
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\nHBM (High Bandwidth Memory) — stacked DRAM, through-silicon vias, wide interfaces, and near-compute memory integration, relevant to AI accelerators, GPUs, HPC, and data-center workloads.
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\nGDDR (Graphics Double Data Rate) — covering the GDDR5, GDDR6, and GDDR7 lineage, relevant to discrete GPUs, gaming, and bandwidth-intensive graphics or compute systems.
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\nLPDDR (Low Power Double Data Rate) — optimized for compact, power-sensitive integration, relevant to smartphones, tablets, thin laptops, and edge devices.
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\nDDR (Double Data Rate) — covering the DDR1–DDR5 lineage, relevant to servers, PCs, workstations, and general-purpose compute platforms.
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Where generation-level data exists, users can drill down further, for example, comparing HBM3E against HBM3, or LPDDR5X against LPDDR5.
Details on all technology packages in the IPlytics platform can be found here.
Built for More Than Just Search
Alongside search and filtering, the package supports:
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Ownership rankings to identify leading innovators and patent holders in each landscape.
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Portfolio benchmarking across companies and technology generations.
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Litigation trend review to support licensing, legal, and patent strategy workflows.
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Row-level exports and analytics views for visual breakdowns and comparisons.
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Why This Matters
Memory technologies are no longer a back-office component, they're increasingly load-bearing for AI accelerators, HPC, data centers, graphics processing, and mobile devices. As performance and power requirements tighten, patenting activity around memory interfaces, controllers, packaging (e.g., TSV, interposers), and signaling schemes is becoming more strategically important to track.
This matters because self-declared essentiality at standards bodies like JEDEC is often incomplete. Declarations are frequently over-broad, outdated, or simply missing, which means they don't reliably reflect who actually holds relevant patents. The Memory technology package addresses this gap directly by classifying and organizing patents into structured landscapes (by memory type and, where available, by generation) giving users visibility independent of what's been formally declared.
With this package, teams can now:
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Prepare for licensing discussions with a clear view of the relevant patent landscape.
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Assess relative portfolio position and strength across covered standards.
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Compare leading innovators and portfolio concentration for competitive intelligence.
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Track litigation trends and assertion patterns across memory-related portfolios.
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Identify where patenting activity is concentrated across HBM, GDDR, LPDDR, and DDR for technology strategy.
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Note: As with all IPlytics technology packages, results and analytics from the Memory package are intended for research and analysis purposes. They should not be treated as legal conclusions on patent essentiality, validity, infringement, or licensing obligations, and legal questions should always be reviewed by qualified counsel.
How to Access the New Data
The Memory technology package is a licensed add-on to the IPlytics Platform and is not included automatically in every standard platform subscription. To request access, contact your IPlytics account manager or reach out to the IPlytics team.
Questions or Feedback?
If you have questions about this new package or need help getting started, our support team is here to help. Contact us at support@lexisnexisip.com.
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The PatentSight Dataset now includes Firmographics (Add-On), otherwise known as Firmographics identifiers that help connect patent intelligence with broader business and financial datasets. Available as an optional add-on, this enhancement enables organizations to enrich patent data with valuable company-level context and create stronger links between intellectual property, ownership structures, and enterprise data ecosystems.
The new firmographic identifier dataset is refreshed weekly and is available for customers accessing PatentSight Dataset - Firmographics through Databricks or Delta Sharing (via a token).
What's New?
Customers can now access a comprehensive set of firmographic identifiers alongside the PatentSight Dataset, including:
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Security Identifiers:
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Financial Instrument Global Identifier (FIGI)
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Stock Ticker Symbols
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Company Identifiers:
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Legal Entity Identifiers (LEI)
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As well as CIK, CRD, JCN, UKCH, RSSD, EIN, and BIC identifiers.
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These identifiers are mapped through Ultimate Owner relationships, making it easier to connect patent portfolios with corporate entities and ownership hierarchies.
This capability is available as an optional upsell to the existing PatentSight Dataset subscription.
Why It Matters
Adding firmographic identifiers to the PatentSight Dataset helps organizations:
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Connect patent intelligence with financial, market, and business datasets
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Link patent assets to ultimate parent companies and ownership structures
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Improve analytics and reporting across enterprise systems
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Support investment research, competitive intelligence, and strategic decision-making
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Simplify integration with internal data warehouses, business intelligence platforms, and third-party data sources
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By providing a common set of business identifiers, customers can more easily combine patent data with other enterprise datasets to gain deeper insights into innovation activity and company performance.
How to Access the Data
The firmographic identifier dataset is available as an add-on purchase for the PatentSight Dataset delivered through:
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Databricks
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Delta Sharing
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Customers interested in adding firmographic identifiers to their existing PatentSight data subscription should contact their LexisNexis Intellectual Property account representative or customer success manager for pricing and availability. Similarly, if you're interested in learning more about our Data Products, please reach out here.
Summary
The addition of firmographic identifiers extends the value of the PatentSight Dataset by helping organizations connect patent intelligence with broader business and financial information. Through weekly refreshed identifier mappings and Ultimate Owner relationships, customers can integrate patent data more effectively into enterprise analytics, reporting, and decision-making workflows.
"},{"id":51166406407827,"url":"https://lnip.zendesk.com/api/v2/help_center/en-us/articles/51166406407827.json","html_url":"https://support.lexisnexisip.com/hc/en-us/articles/51166406407827-Prot%C3%A9g%C3%A9-Release-5-May-2026","author_id":26222564335507,"comments_disabled":false,"draft":false,"promoted":false,"position":0,"vote_sum":0,"vote_count":0,"section_id":48955306675219,"created_at":"2026-04-27T11:03:37Z","updated_at":"2026-05-08T02:35:19Z","name":"Protégé Release (5 May, 2026)","title":"Protégé Release (5 May, 2026)","source_locale":"en-us","locale":"en-us","outdated":false,"outdated_locales":[],"edited_at":"2026-05-05T09:37:39Z","user_segment_id":null,"permission_group_id":20301510583827,"content_tag_ids":[],"label_names":[],"body":"
Period covered: Improvements delivered over the last four weeks.
Faster analytical workflows through parallel conversations
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More robust and predictable analysis experience across visualisation, interaction, and platform behaviour.
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The objective is to remove friction in exploratory work while increasing confidence in outputs and system behaviour. Analysts can move between questions without interruption and rely on clearer, more consistent interactions and results.
This is most impactful for:
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Exploratory analysis: Parallel conversations
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Interpretation quality: Chart robustness and clarity
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Workflow continuity: Query readability and handover
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Work Faster Across Questions\n
What has changed?
Protégé now supports multiple active conversations within a single browser tab, allowing analysts to explore different analytical directions in parallel. The conversation overview has been updated to clearly indicate which conversations are still generating responses and which are complete.
Why it matters
Patent analysis is inherently exploratory and multi-threaded. Analysts often investigate adjacent technologies, compare alternative segments, or pursue separate lines of reasoning at the same time.
A single-threaded interaction model forces sequential work, introducing artificial waiting time and breaking analytical momentum.
Parallel conversations remove this constraint, enabling continuous exploration across multiple lines of inquiry and increasing overall analytical throughput.
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\nAnalytical behaviour
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Multiple conversations can run concurrently within one session
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Each conversation streams responses independently
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Conversations in progress are indicated with a spinner
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\nConstraints & implications
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In-progress responses cannot be cancelled individually
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Conversations are not synchronised across devices or sessions
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Strict correctness guarantees apply:
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All streamed content is scoped to its originating conversation
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No cross-conversation leakage is permitted
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Responses render in the correct order within each conversation
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Example
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A patent analyst investigating how Pfizer’s patent portfolio has evolved post-Covid explores this question from multiple analytical angles in parallel, rather than committing to a single approach upfront:
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One conversation analyses portfolio size and filing trends over time, examining changes in publication volume and growth rates before, during, and after Covid
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Another conversation assess technology composition, identifying shifts in focus areas such as vaccines, mRNA technologies, or adjacent therapeutic domains
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A third evaluates portfolio strength and impact, using indicators such as citations or Patent Asset Index to understand whether Pfizer’s post-Covid activity reflects expansion, consolidation, or quality shifts
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While these analyses run simultaneously, the analyst can see at a glance signaled by a spinner which conversations are still generating insights and which are complete, allowing them to move between lines of inquiry without waiting or losing context.
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More Reliable and Predictable Analysis Experience\n
What has changed?
A set of improvements has been introduced across visualisation, query handling and interaction design to make Protégé outputs and behaviour more consistent and easier to interpret.
Why it matters
Analysts rely on Protégé outputs for decision-making and stakeholder communication. Unclear visuals, limited query visibility, or inexplicit interaction behaviour introduce friction and reduce confidence.
These updates improve clarity, reduce ambiguity, and make workflows more predictable from exploration through to reporting.
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Analytical behaviour
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Charts handle negative values more explicitly where applicable
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Data grouping excludes undefined ultimate owners labeled as <unknown>
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Prompt input is auto-focused after sign-in and when starting a new conversation
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Long search queries are fully readable within the interface
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More prominent way to open queries directly in Custom Analysis
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Example
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A patent analyst reviewing a complex query can now read the full syntax directly in Protégé, and open it in Custom Analysis for further refinement:
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Protégé now also presents results using charts that clearly reflect edge cases such as negative values.
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Protégé will also now filter out unknown ultimate owners:
The goal is practical: manage work in progress with less friction, trust how web and query driven outputs are produced, and complete day to day analysis with fewer dead ends.
Most impactful for:
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Exploratory work - parallel conversations, conversation management, and better continuity across sessions
Traceability and defensibility - query transparency for document level insights
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Richer Patent Data with New Data Fields\n
What has changed?
Protégé now incorporates additional patent-level data fields related to citations, annuity fees, and legal events, expanding the underlying data available for analysis.
Why it matters
For patent analysts, technical relevance alone is rarely sufficient. Understanding how a patent is used, maintained, and evolves legally is often what determines its real strategic value.
These new data dimensions enable more nuanced assessments across three critical lenses:
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Citations: indicators of technological influence and knowledge flow
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Annuity fees: signals of portfolio maintenance decisions and perceived asset value
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Legal events: visibility into lifecycle changes such as pending, in force, in active
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Together, this moves Protégé closer to supporting portfolio quality and lifecycle analysis.
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Analytical behaviour Protégé can now incorporate these fields when retrieving, filtering, and explaining results. This enables:
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surfacing patents with high citation relevance when assessing influential technologies or key prior art
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referencing legal events to contextualise changes in status, ownership, or enforceability
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grounding answers in both technical and legal lifecycle signals, rather than relying solely on publication data
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\n
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Constraints and implications These fields improve analytical depth but should be interpreted with care:
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Citation signals are directional, not definitive indicators of value or validity
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Legal event interpretation remains context-dependent and does not replace formal legal assessment
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The feature therefore strengthens contextual understanding, rather than acting as a standalone legal evaluation tool.
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Example An analyst assessing a competitor portfolio can now go beyond identifying relevant patents to:
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check which assets appear in force versus inactive or pending, indicating strategic commitment
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highlight who cites the portfolio, checking technological relevance
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Better Conversation Management with Rename, Delete, and Retention Transparency\n
What has changed?
Users can now rename and delete auto-saved conversations. Protégé also introduces a 90 day retention policy for conversations, with prior notification before deletion.
Why it matters
This improves continuity for ongoing work while helping users keep their workspace organised. It also makes data retention behaviour clearer and more predictable.
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Analytical behaviour Users can now: a) reopen recent conversations with context restored, b) rename conversations to reflect the analytical topic, c) delete conversations that are no longer useful Conversations older than 83 days are marked as Pending Deletion, and users are notified 7 days before automatic deletion.
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Constraints and implications Conversation history is retained for 90 days from creation date and then deleted automatically. Deleted conversations are not recoverable.
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Example An analyst renames a conversation from a generic timestamp to \"Waymo’s patent portfolio\", making it easier to return to the work later. Older exploratory threads can be deleted to keep the workspace focused.
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Improved Patent Number Matching\n
What has changed?
Protégé now matches patent numbers more robustly, including incomplete or differently formatted variants, and aligns matching logic more closely with PatentSight+ where feasible.
Why it matters
Patent analysts often work with inconsistent patent number formats. Better matching reduces manual rechecking and improves continuity between Protégé and PatentSight+.
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Analytical behaviour Protégé now:
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accepts more valid patent number variants
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normalises input into a canonical matching form
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attempts to resolve inputs to a unique PatentSight patent identifier
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presents disambiguation when multiple plausible matches exist
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provides clearer feedback when no plausible match is found
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Constraints and implications This release improves number matching, but does not add bulk import flows.
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Example An analyst enters a list of patent numbers without kind codes or with unusual separators. Protégé can still resolve the intended patent document, or guide the user to refine the input if ambiguity remains.
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\n
\n
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Better Intent Recognition for Simple Tasks\n
What has changed?
Protégé is now better at identifying simple requests and avoiding unnecessary complex analysis when a straightforward answer is sufficient.
Why it matters
Not every task needs a multi-step analysis plan. By responding more proportionately to simple requests, Protégé can answer faster and fail less often.
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Analytical behaviour For tasks where a direct number or simple factual response is sufficient, Protégé now aims to avoid over analysing, over explaining, or invoking more complex reasoning than necessary.
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Constraints and implications This optimisation is intended for clearly simple tasks. More interpretive or multi-dimensional questions still require broader reasoning and explanation.
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Example If an analyst asks for the number of patents in a narrowly defined set - for instance owner Nintendo - Protégé no longer overcomplicates the task with unnecessary thinking and contextualising, but returns the number.
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Lower Task Failure Rates and Clearer Recovery Behaviour\n
What has changed?
Protégé now includes better failure detection, classification, user messaging, and observability to reduce task failures and make recovery clearer when completion is not possible.
Why it matters
Reliability is not only about completing successful tasks. It is also about being honest and useful when something goes wrong. This release aims to reduce dead ends while helping engineering teams monitor and improve failure patterns systematically.
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Analytical behaviour Protégé now:
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detects and logs incomplete task outcomes more clearly
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classifies failure types such as ambiguity, system error, unsupported capability, and safety restriction
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presents clearer user facing explanations when tasks fail
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suggests practical next steps such as retrying, narrowing scope, rephrasing, or switching workflow
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Constraints and implications This release improves handling and observability of failures. The focus is on reducing hard failures and making failure states more transparent and actionable.
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Example If a request is too ambiguous to complete safely, Protégé now explains what is unclear and suggests how to refine the input rather than guessing silently or stalling.
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Parallel Conversations for Exploratory Analysis\n
What has changed?
A single user can now run multiple conversations in parallel in Protégé by opening multiple tabs in the same web browser. Responses stream independently into the corresponding browser tab.
Why it matters
Patent analysis is rarely linear. Analysts often want to pursue a follow up question or adjacent topic while another answer is still being generated. Parallel conversations reduce waiting time and better match real exploratory workflows.
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Analytical behaviour Submitting a prompt in one conversation no longer blocks work. Streaming responses are routed to their originating browser tab, and failures in one conversation do not interrupt others.
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Constraints and implications This release enables parallel work, but does not yet include parallel conversation in one browser tab, per conversation cancellation, live synchronisation across devices, or a broader redesign of conversation navigation.
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Example While Protégé is generating a response on Battery Materials, an analyst can open a new browser tab and start a second conversation by asking about Main competitors in solid state electrolytes without waiting for the first answer to finish.
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What this article covers
\n
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Explains how Classifiers are exported and synchronised from the LexisNexis Classification platform into PatentSight+ for analysis. (Note - this article is only relevant for those building Classifiers to be used in the LexisNexis PatentSight+ platform for reporting and analysis.)\n
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Describes how on-demand export, automatic re-synchronization, and export status tracking ensure classifier data remains up to date.
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Shows how synchronized classifiers can be verified and accessed in PatentSight+ for use in searches, dashboards, and analyses.
Classifiers are now available within the Patentsight+ platform. Classifiers are built within the LexisNexis Classification platform and can be synchronized into PatentSight+, where they are used to generate insights and analyses on patent data.
This synchronization ensures that relevant patent families, identified through the classifier, are made available in PatentSight+ for review and reporting.
As part of this process, classifier data is exported based on defined rules to ensure accurate and meaningful analysis within PatentSight+.
This article explains how synchronization works for classifier builders and how classifier data becomes available in PatentSight+.
Note: This article is only relevant for users who utilize PatentSight+ to analyse and report on Classifiers.
On-Demand Synchronization of Classifier Data to PatentSight+
Classifiers built in the LexisNexis® Classification™ platform must be exported to LexisNexis® PatentSight+™ before they can be used for analysis.
On-Demand Synchronization enables classifier owners to export classifiers immediately and automatically keep them up to date when changes occur, and monitor export status. On-Demand synchronization is a setting that needs to be enabled and we walk through this, in the article below.
This gives classifier owners full control over when a classifier is exported and how updates are propagated to PatentSight+.
Note: Only the Classifier owner (or those with edit access within the Classification platform) can export it to PatentSight+. If you are not the owner, or do not have edit access, please contact the Classifier owner, or your Admin, to request export.
How Synchronization Works
A Classifier is exported to PatentSight+ for the first time via manual trigger (what we refer to as On-Demand sync) by either the Classifier owner or those with edit access to it. Then it can be kept up to date through a combination of:
The Classifier builder should log into the Classification platform and click the 'Classifier training' tile. This is where Classifiers are built:
Open your Classifier and click “Export”. (Alternatively, navigate directly to Classifiers → Library)\n
In the PatentSight+ Export Status column, click the blue synchronization icon.
Follow the on-screen dialog and click “Begin.” The system will refresh the selected Classifier with the most recent data from the Classification Platform into PatentSight+.
Synchronization is not instantaneous. Processing time depends on the classifier size and the number of simultaneous requests, and may take from several minutes up to approximately one hour. During this time, the export runs asynchronously in the background.
Automatic Re-Synchronization
Once a Classifier has been exported, it can be kept up to date automatically through auto re-synchronization.
When auto re-sync is enabled, the classifier is automatically re-exported to PatentSight+ when:
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The classifier is rebuilt
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Patent data updates occur (weekly after our internal data updates)
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\nClassifier metadata changes, including:
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Classifier name
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Taxonomy path
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Scope
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Auto re-synchronization is switched off by default, and can be switched on or off per classifier.
When auto re-sync is disabled, the classifier will only be updated when the owner manually triggers an export. This allows customers to maintain a stable version of a classifier in PatentSight+ when required.
How to enable Auto Re-Sync
This can be done from within each Classifier, or in the library view.
To enable from within the Classifier, select the cog icon next to 'Export' and select the box to 'Enable Auto Re-Sync'.
To enable from within the library view, select the Classifier or Classifiers you want to update via the blue tick. In the image below, three Classifiers are selected. Then select the arrow next to 'Actions' and select to 'Enable Auto Re-Sync'.
Tracking the Export Status
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\nThe Export Status displays real-time progress of the export and synchronization process.\n
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If the export fails, the system will automatically retry two additional times.
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After three unsuccessful attempts, an error status will be shown.
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Possible reasons for export failure include:
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The evaluation landscape report has not been updated since the last modifications to the Classifier or is missing.
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The training set is too small to meet export requirements.
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The Classifier is too broad in scope.
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Verify the export date in PatentSight+
In PatentSight+, you can verify that synchronization has completed by checking:
‘Last Exported’ – the most recent successful export date, under Option → Manage Access for AI Classifiers.
Note - In this section you can also see when the Classifier was last modified/re-built in the 'Last Built' Column.
Accessing the Synchronized Classifier in PatentSight+
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In PatentSight+, open the filter menu and click the “+” icon.
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Search for and select 'AI Classifier'.
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Choose your classifier from the list or from the taxonomy tree.
If a taxonomy is set up, you can select an individual classifier or an entire taxonomy node to include multiple classifiers.
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Summary
On-demand synchronization ensures that Classifiers in PatentSight+ reflect the latest data from the LexisNexis Classification Platform.
Classifier owners can export classifiers immediately, enable automatic re-synchronization to keep classifiers up to date, and track synchronization progress and status directly in the platform.
If you are a classifier owner, you can export and synchronize directly. If you use shared classifiers, contact your Admin or Classifier Owner to initiate synchronization. Keeping classifiers current ensures that your PatentSight+ searches, dashboards, and analyses reflect the most accurate data available.
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LexisNexis® offers a range of intellectual property data products designed to support different use cases across the patent lifecycle from raw patent data ingestion to advanced analytics, litigation intelligence, and prosecution strategy.
This guide helps you determine which dataset is right for your needs, based on the type of data you require, how you want to use it, and how you plan to integrate it into your systems.
Choosing the right dataset depends on your data needs, use cases, and integration requirements. If you want to learn more and discuss your specific needs after reviewing the FAQs below, please complete this form and a member of the team will reach out to you.
FAQs
What is the difference between IP DataDirect and PatentSight+™ Bulk Data?
The key difference is the level of data and intended use:
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IP DataDirect provides document-level patent data, including global patent publications, legal status, and metadata. Best for building internal patent databases or search systems.
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PatentSight+ Bulk Data provides patent family–level analytics data, including ownership, technology classifications, and proprietary metrics. Best for portfolio analysis, benchmarking, and strategic insights.
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If you need raw patent data, choose IP DataDirect. If you need analytics-ready patent intelligence, choose PatentSight+ Bulk Data.
When should I use the Global Patent Litigation Dataset?
You should use the Global Patent Litigation Dataset (GPLD) when you need visibility into patent disputes and litigation risk. It is best suited for:
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Monitoring litigation activity across jurisdictions
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Assessing risk in M&A or patent acquisitions
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Tracking competitor enforcement strategies
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Analyzing litigation outcomes and trends
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Choose GPLD when your focus is litigation, disputes, and risk analysis.
What is the difference between the Global Patent Litigation Dataset (GPLD) and PatentAdvisor® API?
These datasets cover different stages of the patent lifecycle:
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GPLD focuses on litigation (what happens after a patent is enforced or challenged)
\n
PatentAdvisor API focuses on prosecution (what happens during patent examination)
\n
Use GPLD to analyze litigation risk and disputes. Use PatentAdvisor API to optimize filing strategy and predict examiner behavior.
Many organizations use both together to understand end-to-end IP risk and strategy.
Which dataset should I use for building my own patent database?
Use IP DataDirect. It provides:
\n
Global patent publications
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Full-text documents
\n
Legal status data
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Standardized XML formats
\n
It is specifically designed for data ingestion, storage, and internal system integration.
Which dataset is best for patent portfolio analysis and benchmarking?
Use PatentSight+ Bulk Data. It includes:
\n
Patent family–level data
\n
Corporate ownership mapping
\n
Technology clustering
\n
Metrics such as Patent Asset Index
\n
It is designed for analytics, benchmarking, and strategic decision-making.
Can I combine multiple datasets?
Yes. Many organizations use multiple datasets together. For example:
\n
IP DataDirect to build a patent data foundation
\n
PatentSight+ Bulk Data to perform analytics and benchmarking
\n
GPLD to assess litigation risk
\n
PatentAdvisor API to optimize prosecution strategy
\n
Combining datasets allows organizations to build a complete view of the patent lifecycle, from filing through to litigation.
Which dataset is right for data science or machine learning projects?
It depends on your objective:
\n
Use IP DataDirect if you need large-scale raw patent data for NLP, text mining, or custom models
\n
Use PatentSight+ Bulk Data if you need structured, analytics-ready data with metrics
\n
Use GPLD if you want to model litigation risk or outcomes
\n
Use PatentAdvisor API if you want to model prosecution success or examiner behavior
\n
How do I decide which dataset is right for my organization?
Ask yourself the following:
1. What type of data do I need?
\n
Raw patent documents → IP DataDirect
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Patent analytics → PatentSight+ Bulk Data
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Litigation data → GPLD
\n
Prosecution data → PatentAdvisor API
\n
2. What is my primary use case?
\n
Build internal patent systems → IP DataDirect
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Portfolio benchmarking → PatentSight+ Bulk Data
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Litigation risk analysis → GPLD
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Filing strategy optimization → PatentAdvisor API
\n
3. How do I want to use the data?
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Store and manage data internally → IP DataDirect
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Analyze and visualize insights → PatentSight+ Bulk Data
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Integrate litigation intelligence → GPLD
\n
Integrate prosecution analytics → PatentAdvisor API
\n
Who typically uses these datasets?
These datasets are commonly used by:
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IP and R&D professionals
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Legal and compliance teams
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Financial analysts and investment teams
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Enterprise data and analytics teams
\n
Data scientists and engineers
\n
Where can I learn more about each dataset?
You can explore detailed articles for each product:
LexisNexis IP data products are designed to support different stages of the patent lifecycle and different types of analysis.
\n
IP DataDirect > raw patent data
\n
PatentSight+ Bulk Data > patent analytics
\n
Global Patent Litigation Dataset > litigation intelligence
\n
PatentAdvisor API > prosecution analytics
\n
Choosing the right dataset depends on your data needs, use cases, and integration requirements. If you want to learn more and discuss your specific needs after reviewing these FAQs, please complete this form and a member of the team will reach out to you.
The LexisNexis PatentAdvisor® API provides structured access to U.S. patent prosecution data, enabling you to integrate examiner analytics and prosecution insights directly into your internal systems, analytics platforms, and workflows.
The dataset covers more than 10.5 million USPTO patent applications dating back to 2001, providing detailed insights into examiner behavior, office actions, and prosecution outcomes. It includes proprietary analytics designed to help you understand how patent applications are reviewed and how likely they are to be granted.
A key feature of the dataset is the Examiner Time Allocation (ETA) metric, which predicts both the likelihood and timing of patent approval based on historical examiner behavior.
PatentAdvisor® API is used to forecast prosecution outcomes, optimize filing strategies, evaluate examiner behavior, and analyze office actions and appeals.
It is typically used by patent attorneys, in-house IP and R&D teams, law firms, and enterprise data and analytics teams integrating prosecution insights into internal systems.
By providing structured, analytics-ready data, PatentAdvisor® API enables more informed decision-making throughout the patent filing process.
How does it differ from the LexisNexis PatentAdvisor® platform?
The LexisNexis PatentAdvisor® platform is a SaaS application that provides interactive tools, dashboards, and visualizations for analyzing patent prosecution and examiner behavior.
The PatentAdvisor® API, by contrast, provides direct access to the underlying prosecution dataset, allowing you to integrate this data into your own tools, workflows, and analytics environments.
This allows you to:
\n
Combine prosecution data with internal business or portfolio data
\n
Build custom dashboards and reporting tools
\n
Automate prosecution analysis workflows
\n
Integrate insights into internal systems and applications
\n
Many organizations use both solutions together involving the use of the PatentAdvisor platform for interactive analysis, while leveraging the API for deeper integration and automation.
Data Delivery Options
PatentAdvisor® API is delivered through a real-time API, enabling you to retrieve and integrate prosecution data directly into your systems.
API Access
The API provides:
\n
Real-time access to USPTO prosecution data
\n
Structured application and examiner-level data
\n
Integration into internal tools, applications, and analytics platforms
\n
Ability to filter and monitor applications by examiner, art unit, and other criteria
\n
This allows you to embed prosecution insights directly into your workflows and automate data retrieval and analysis.
The LexisNexis PatentAdvisor® API provides direct access to one of the most comprehensive U.S. patent prosecution datasets available.
By delivering structured examiner analytics, prosecution data, and predictive metrics such as ETA through a real-time API, it enables you to integrate prosecution intelligence directly into your systems and workflows.
This makes PatentAdvisor® API an ideal solution for organizations seeking data-driven prosecution strategy, improved filing outcomes, and deeper integration of patent insights into their analytics environments.
"},{"id":49960191054867,"url":"https://lnip.zendesk.com/api/v2/help_center/en-us/articles/49960191054867.json","html_url":"https://support.lexisnexisip.com/hc/en-us/articles/49960191054867-LexisNexis-Global-Patent-Litigation-Data","author_id":26222564335507,"comments_disabled":false,"draft":false,"promoted":false,"position":0,"vote_sum":0,"vote_count":0,"section_id":42815012533395,"created_at":"2026-03-16T11:46:12Z","updated_at":"2026-04-30T14:13:49Z","name":"LexisNexis® Global Patent Litigation Data","title":"LexisNexis® Global Patent Litigation Data","source_locale":"en-us","locale":"en-us","outdated":false,"outdated_locales":[],"edited_at":"2026-04-30T14:13:49Z","user_segment_id":null,"permission_group_id":20301510583827,"content_tag_ids":[],"label_names":[],"body":"
What is the LexisNexis® Global Patent Litigation Dataset?
The LexisNexis® Global Patent Litigation Dataset (also known as GPLD) provides structured access to global patent litigation data collected from courts and intellectual property authorities around the world.
The dataset contains over 600,000 patent-related cases and more than 570,000 litigation documents sourced from 22 countries and authorities and over 500 court and agency websites. It includes both court case documentation and agency proceedings such as opposition filings, opinions, and validity rulings.
GPLD enables you to track when patents are involved in litigation, analyze outcomes where available (such as infringement or invalidation), and identify broader litigation trends across jurisdictions, industries, and companies. It is commonly used to support litigation risk assessment, M&A due diligence, competitor monitoring, and the identification of high-risk patents and technologies, as well as to analyze litigation trends across global markets.
The dataset includes structured fields such as:
\n
Country and court
\n
Parties involved in the case
\n
Judges and attorneys
\n
Litigation outcomes and damages
\n
Associated patent numbers and patent families
\n
Patent owners and product information
\n
Data is collected from global sources daily using a combination of automated collection methods and manual review. Non-English litigation documents are translated, and image-based documents are processed using OCR to extract relevant data fields.
This enables you (typical users include patent attorneys, in-house legal teams, law firms, and enterprise data and analytics teams) to integrate global patent litigation intelligence directly into your internal systems, analytics platforms, and decision-making workflows. For more information on use cases and typical users, see the Use Cases for LexisNexis® Global Patent Litigation Dataset article.
How does it differ from litigation data in other LexisNexis products?
The Global Patent Litigation Dataset (GPLD) provides structured litigation data designed for direct integration into internal systems, analytics platforms, and data pipelines.
Some LexisNexis platforms also contain litigation information within their user interfaces. However, those products are designed primarily for interactive research and analysis, while GPLD provides the underlying data for organizations that want to build their own analytics environments.
GPLD can also be used alongside other LexisNexis litigation data products, such as the LexisNexis PatentAdvisor® API.
While GPLD focuses on global patent litigation data, the PatentAdvisor API provides U.S. patent prosecution insights, including examiner behavior and office action analytics. Together, these datasets allow you to analyze both litigation risk and prosecution strategy across the patent lifecycle.
For example:
\n
GPLD enables you to identify litigation trends, assess litigation risk, and track enforcement activity across jurisdictions.
\n
PatentAdvisor API enables you to analyze examiner behavior and predict patent prosecution outcomes.
\n
Together, these datasets provide a more complete view of intellectual property risk, strategy, and decision-making.
Data Delivery Options
The Global Patent Litigation Dataset is designed for integration into modern analytics and data environments.
Databricks Data Platform
GPLD can be accessed through Databricks Marketplace, enabling organizations to query and analyze litigation data within their existing analytics workflows.
Delta Sharing
You can also access the dataset through Delta Sharing, an open protocol that allows data to be securely shared across different analytics platforms without requiring a Databricks environment.
This approach enables you to integrate litigation data into your preferred analytics tools or internal data pipelines.
The LexisNexis® Global Patent Litigation Dataset (GPLD) provides structured access to global patent litigation data collected from courts and intellectual property authorities worldwide.
By delivering litigation intelligence that can be integrated directly into internal analytics platforms and data pipelines, GPLD enables you to assess litigation risks, monitor competitor activity, and support strategic intellectual property decisions.
This makes GPLD an ideal solution where you require enterprise-scale litigation intelligence integrated into your internal analytics environments.
If you have more questions, please do reach out and let us know what data challenge we can lend support toward.
LexisNexis® PatentSight+™ Bulk Data provides direct access to the curated patent analytics datasets that power the PatentSight+ platform. It is designed for you to integrate patent intelligence into your internal analytics environments, business intelligence tools, or data science workflows.
Unlike document-level patent datasets, PatentSight+ Bulk Data is structured at the patent family level, allowing you to analyze inventions across jurisdictions as a single innovation unit. The dataset combines harmonized patent family data with normalized corporate ownership information, technology classifications, and proprietary patent analytics metrics.
PatentSight+ Bulk Data enables you to perform large-scale patent analytics within your own systems, supporting strategic decision-making across intellectual property management, R&D strategy, competitive intelligence, and market analysis.
The dataset includes curated modules covering:
\n
Core patent family and bibliographic data
\n
Technology landscape classifications and clustering
\n
Patent lifecycle and legal status indicators
\n
Corporate ownership and portfolio attribution
\n
Advanced patent analytics metrics such as LexisNexis® Patent Asset Index, Technology Relevance, and Market Coverage
\n
These datasets are designed for integration into enterprise analytics platforms, enabling you to build your own dashboards, reports, and analytical models.
PatentSight+ Bulk Data supports use cases such as technology landscape analysis, competitive benchmarking, innovation strategy, and portfolio valuation, as well as integration into internal analytics environments. It is typically used by IP, strategy, and R&D professionals, along with financial analysts and enterprise data teams, who need structured patent intelligence to support advanced analytics and decision-making.
How does it differ from the LexisNexis® PatentSight+™ platform?
PatentSight+ Bulk Data and the PatentSight+ platform are built on the same underlying patent analytics data but serve different purposes.
The LexisNexis® PatentSight+™ platform is a SaaS application that provides ready-made analytics dashboards and visualizations for patent portfolio analysis, benchmarking, and technology landscape exploration.
PatentSight+ Bulk Data, by contrast, provides direct access to the underlying curated datasets. It is designed for you to integrate patent analytics into your own internal tools, business intelligence platforms, or data science environments.
This allows you to:
\n
Combine patent intelligence with internal business data
\n
Build custom dashboards and analytical models
\n
Integrate patent analytics into enterprise BI environments such as Power BI or Tableau
\n
Run large-scale data science workflows and machine learning analysis
\n
Many organizations use both solutions together, using the PatentSight+ platform for interactive analysis while leveraging PatentSight+ Bulk Data for deeper integration with internal analytics environments.
Data Delivery Options
PatentSight+ Bulk Data can be delivered through several mechanisms depending on your technical environment and integration requirements.
Databricks Data Platform
PatentSight+ datasets can be accessed through a managed Databricks data environment, enabling you to query and analyze patent intelligence directly within your existing analytics workflows.
Bulk Data Exports
Curated datasets can also be delivered through structured CSV exports, allowing you to ingest patent analytics data into your internal data warehouses or analytics platforms.
API Integration
For automated workflows, API-based access allows datasets to be integrated into internal applications, reporting pipelines, or analytics environments.
PatentSight+™ Bulk Data provides you with direct access to the curated patent analytics datasets that power the PatentSight+ platform.
By delivering harmonized patent family data, ownership intelligence, and proprietary patent analytics metrics in flexible formats, PatentSight+ Bulk Data enables you to integrate patent intelligence directly into your analytics platforms and decision-making workflows.
This makes it an ideal solution if you require enterprise-scale patent analytics, custom reporting, and deep integration with internal data environments.
Please do reach out and let us know what data challenge we can lend support toward.
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LexisNexis® IP DataDirect (IPDD) is a bulk patent data delivery platform that gives you direct access to one of the world’s largest collections of patent information.
The platform enables you to access a curated repository of global patent data, including full-text documents, images, legal status data, and enriched metadata. With coverage from more than 109 patent authorities and over 178 million documents, IP DataDirect provides comprehensive patent information to support large-scale research, analytics, and internal data integration.
IP DataDirect removes the complexity of collecting and standardizing patent data from multiple offices by delivering harmonized datasets you can integrate directly into your systems and workflows. Patent publications are delivered in standardized XML formats aligned with WIPO ST.36, enriched with value-added elements such as machine translation, normalized entity names, legal status information, and patent family data.
New and updated patent publications are made available in near real-time, ensuring you have access to the most up-to-date patent information.
IP DataDirect supports a wide range of use cases, including patent search and analysis, technology landscape monitoring, competitive benchmarking, and the integration of patent data into internal systems for large-scale analytics and machine learning. It is typically used by IP and R&D professionals, legal and compliance teams, financial analysts, and enterprise data teams who require high-quality, structured patent data to power advanced research, analytics, and business decision-making.
How does it differ from the LexisNexis® PatentSight+™ platform?
While both IP DataDirect and PatentSight+ leverage high-quality LexisNexis patent data, they serve different purposes.
PatentSight+ is a SaaS platform that provides ready-to-use analytics dashboards and built-in metrics for analyzing patent portfolios, benchmarking innovation, and exploring technology landscapes.
IP DataDirect, by contrast, provides direct access to the underlying patent data itself. It is designed for organizations that want to integrate patent information into their own internal tools, databases, or analytics environments.
This makes IP DataDirect particularly useful for organizations that want to:
\n
Maintain internal patent databases
\n
Build custom analytics or data science workflows
\n
Integrate patent intelligence into BI platforms such as Power BI or Tableau
\n
Combine patent data with internal business or research datasets
\n
Many organizations use both solutions together, using PatentSight+ for interactive portfolio analysis while leveraging IP DataDirect for deeper integration with internal systems and data pipelines.
Data delivery options
IP DataDirect provides flexible delivery options to support different technical environments and integration needs.
Bulk Data API
You can retrieve complete or partial patent datasets and maintain their own internal patent databases through a structured API or data feed.
Search API
The Search API enables you to directly query the LexisNexis patent collection and retrieve patent data and associated documents for integration into internal systems.
Custom Data Services
For organizations with specialized requirements, LexisNexis can provide customized patent datasets tailored to specific jurisdictions, time ranges, or technical fields.
LexisNexis® IP DataDirect gives you direct access to one of the world’s most comprehensive collections of patent data.
By delivering harmonized, standardized patent information through flexible APIs and bulk data feeds, IP DataDirect enables organizations to integrate high-quality patent intelligence directly into their own systems, analytics platforms, and research workflows.
This makes IP DataDirect ideal if you require large-scale patent data access, custom analytics capabilities, and deep integration with internal data environments.
This month’s release focuses on three core themes:
\n
Clearer query construction
\n
More transparent analysis
\n
More reliable visual outputs
\n
Our goal is simple: Analysts should be able to clearly see what Protégé is doing, understand why results look the way they do, and refine their analysis without unintended side effects.
These enhancements are especially impactful for:
\n
Daily analysis — Improved concept-based queries and greater chart reliability
Time-sensitive questions — Added web search context for stronger, faster answers
\n
Clearer Query Construction\n
What has changed?
Protégé now constructs queries from explicit, modular concepts rather than implicit keyword groupings.
Why it matters
This reduces query drift and makes iterative refinement auditable without destabilising prior results.
\n
Analytical behaviour Queries are represented as modular concept blocks. Editing one concept (e.g., battery materials) leaves others (e.g., manufacturing processes) unchanged. Segment analysis allows controlled expansion via umbrella / sub‑domain relationships, preserving anchor terms.
\n
Intent Make complex searches composable and auditable, so analysts can iterate quickly while maintaining traceability and minimizing query drift.
\n
\n
Constraints & implications
\n
\n
Results are attributed at the concept level, enabling per‑concept reasoning summaries
\n
Expanding a concept increases recall but may change comparability with prior runs
\n
Concept boundaries, not raw keywords, now anchor analysis
\n
\n
\n
Example An analyst replaces “energy storage” with the sub‑domain “solid‑state electrolytes” while keeping manufacturing and geography concepts unchanged, preserving comparability with earlier analyses.
\n
Increased Transparency Through Reasoning Summaries\n
What has changed?
Protégé now provides structured reasoning summaries alongside insights, separated from the final conclusions for easier review.
Why it matters
This improves defensibility: analysts can validate how an insight was formed before sharing it with stakeholders or reusing it in a repeatable workflow.
\n
Analytical behaviour Protégé attaches a concise reasoning summary that explains the steps behind the conclusion. Reasoning is logically separated from the main insight to make scanning and auditing easier.
\n
Constraints & implications Summaries reflect high‑level analytical steps (e.g., “filtered by concept A, grouped by reporting date, compared top decile vs median”), not raw model internals, to balance transparency with clarity.
\n
\n
Example An analyst asks: “Which assignees are strengthening positions in solid‑state batteries over time?” Protégé returns an insight and a reasoning summary indicating it:
\n\n
filtered by the concept solid‑state electrolytes,
\n
grouped results by reporting year, and
\n
compared top‑decile assignees against the median trend.
\n\n
\n
The analyst can now copy the insight into a slide with a defensible “method line” that matches the analysis.
\n
\n
\n
More Reliable and Readable Charts\n
What has changed?
Charts are now clearer, more consistent, and more faithful to the underlying results and narrative.
Why it matters
This reduces cognitive load and lowers the risk of misleading visual inference—especially when analysts compare trends across time, segments, or entities.
\n
Analytical behaviour Each query renders one primary visualization for focus. Results can be grouped by reporting date to highlight temporal patterns. Line charts render linear timeline (e.g., no year gaps). Bubble charts have labels and adjusted axis to improve readability. Textual explanations of charts are synchronized with what is on screen.
\n
Constraints & implications Narrative generation is constrained to visible aggregates and acknowledged gaps, improving faithfulness and limiting hallucinated trends.
\n
Example A line chart showing patent publications by year (2015-2025) will show no visual gap when 2020 is zero. The accompanying text will state “no publications in 2020” rather than implying a continuous trend.
\n
\n
\n
\n
Up‑to‑Date Context via Web Search Integration\n
What has changed?
Protégé can now use a web search endpoint to retrieve fresher context when recency is likely to materially affect the answer.
Why it matters
This reduces drift on time‑sensitive topics (e.g., recent company activity), while keeping core analytical behaviour stable and predictable.
\n
Analytical behaviour Web search is invoked selectively when recency is likely to change an answer. Where available, responses include links or references to consulted sources.
\n
Constraints & implications Addition reduce drift on time‑sensitive topics, while keeping the core analytical model stable.
\n
Example When assessing recent competitor activity, Protégé may consult public sources to contextualise an insight, then provide links so the analyst can verify recency claims quickly.
\n
\n
\n
\n
Prompt Language Updates\n
What has changed?
Prompts and system phrasing now align more closely with PatentSight+ wording and style, improving consistency in outputs.
Why it matters
More consistent phrasing reduces rework: analysts get responses with a steadier structure, clearer terminology, and fewer “style surprises” across sessions.
Constraints & implications Tighter prompts lead to more stable tone and structure in generated text, improving readability and reducing rework.
\n
Example An analyst running the same type of comparative query across different owners should see more consistent headings, terminology, and summary structure - making results easier to compare and reuse.
\n
Easier Access to Protégé from PatentSight+\n
What has changed?
A new Protégé tile has been added to the PatentSight+ homepage, making it faster to start a new Protégé task.
Why it matters
This reduces friction between resuming structured work (e.g., Customer Analysis) and starting exploratory analysis in Protégé - useful when analysts move from reporting to investigation.
\n
\n
\n
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We’re excited to announce an important update to the Wi-Fi technology package in IPlytics. As part of this enhancement, IPlytics has expanded Wi-Fi 7 (IEEE 802.11be / Extremely High Throughput – EHT) coverage to include patents that are not declared but are relevant to the Wi-Fi 7 standard.
Wi-Fi 7 declared SEPs were already available within the Wi-Fi technology package. This update builds on that foundation by adding IPlytics-identified undeclared Wi-Fi 7 SEPs, providing a more complete and transparent view of the Wi-Fi 7 patent landscape as adoption accelerates.
An undeclared patent is a patent that has not been formally declared as standard-essential to a standards organization or disclosed via a patent pool. IPlytics finds those relevant to the specific technology standard using the LexisNexis Classification methodology.
What’s New
Undeclared Wi-Fi 7 Patent Coverage
The Wi-Fi technology package now includes undeclared patents relevant to Wi-Fi 7, in addition to existing declared and pooled patents.
This expansion adds:
\nUndeclared Patents for Wi-Fi 7 - Patents identified by IPlytics using documented classification approaches and expert validation as relevant to the Wi-Fi 7 (802.11be) standard, even where no formal declaration has been made.
Declared and pooled Wi-Fi 7 SEPs remain unchanged. Together, these layers provide a more comprehensive representation of the Wi-Fi 7 landscape, aligned with how undeclared patent coverage is handled in other IPlytics technology packages.
Why This Matters
Wi-Fi 7 introduces major technical advancements over earlier Wi-Fi generations, including wider channel bandwidths, higher order modulation, and new mechanisms for low latency and high reliability communication. As the standard moves from early deployment toward broader commercial adoption, SEP visibility becomes increasingly critical.
Advanced OFDMA scheduling, including Multiple Resource Units (MRU)
\n
Restricted Target Wake Time (rTWT) for deterministic low latency operation
\n
Because Wi-Fi standards are cumulative, overlap between Wi-Fi 6 and Wi-Fi 7 SEP landscapes is expected and reflects inherited PHY and MAC functionality rather than misclassification.
How to Access the New Data
The undeclared Wi-Fi 7 patent data is available as part of the Wi-Fi technology package in IPlytics. Availability depends on the technologies enabled within your IPlytics environment. If you have questions about access to this update, please contact your LexisNexis Intellectual Property Solutions representative or customer support on support@lexisnexisip.com.
To learn how to search for Undeclared Patents in IPlytics, click here.
Questions or Feedback?
If you have questions about this update or need help interpreting the expanded Wi-Fi 7 landscape, our support team is here to help.
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The difference between declared and undeclared SEPs, and why both are needed for a complete analysis
\n
What a technology package contains
\n
How technology packages are built — the eight-step process combining ML classifiers, LLMs, and analyst review
\n
What the \"undeclared patent landscape\" means in practice, and how it relates to the package you access in the platform
\n
Which technology standards are available across Video, Audio, Cellular, Wi-Fi, Wireless Charging, and Cellular IoT
\n
\n
Why technology packages matter for IPlytics users — practical use cases from licensing to portfolio benchmarking
\n
\n
\n
Overview
A technology package in IPlytics (also called a feature package) is an expertly curated collection of patents covering a specific technology standard — for example, Wi-Fi 6, 5G, or HEVC video compression. It combines declared SEPs (patents formally notified to a standards body) with undeclared SEPs (likely/predicted essential patents identified by machine learning and confirmed by patent experts), giving a complete picture of who holds relevant patents in a given technology area.
Rather than constructing a patent search from scratch, users of the IPlytics platform can access these packages directly to immediately explore which companies hold relevant patents, how many patents exist in the landscape, and which may be essential to a given standard.
Declared vs. Undeclared SEPs
To understand technology packages, it helps to understand Standard Essential Patents (SEPs).
When a standards development organization (SDO) such as ETSI, IEEE, ITU-T, or the Wireless Power Consortium (WPC) publishes a technical standard, companies that own patents believed to be essential to implementing that standard are generally expected to declare those patents to the relevant body. These are known as declared SEPs.
However, not every patent that is technically essential to a standard is formally declared. Some patents are overlooked, acquired after the declaration process, or simply never submitted by their owner. These are commonly referred to as undeclared, predicted, or candidate SEPs.
The IPlytics platform identifies undeclared SEPs using machine-learning models that analyse patent content against standards documents, surfacing patents that may be essential even though they were never formally declared.
Both layers matter for serious analysis. Focusing only on declared SEPs gives an incomplete (and potentially misleading) view of patent ownership, licensing exposure, and competitive positioning. For this reason, technology packages are designed to incorporate both declared and undeclared datasets where available, supporting more accurate licensing analysis, portfolio benchmarking, royalty modelling, litigation assessment, and strategic decision-making.
What a Technology Package Contains
A technology package combines two layers of patent coverage for a given standard:
\n
\nDeclared SEPs — patents formally notified to a standards body by their owners as potentially essential to the standard.
\n
\nUndeclared (predicted) SEPs — patents identified by IPlytics' machine learning and LLM-based methodology as likely essential, even though they have not been formally declared.
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The combination of both layers is what makes a technology package comprehensive. Each package is:
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\nExpert-built, using standards-specific knowledge and datasets
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\nMachine-learning verified, using IPlytics' classification models
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\nAnalyst-reviewed, to ensure quality and relevance
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As a result, users can begin analysing a technology landscape immediately, without needing specialist knowledge of standards documents, declaration databases, or patent search methodologies.
How Technology Packages Are Built
Each technology package is produced through a structured, end-to-end process combining machine learning, large language models (LLMs), and human expert review. This process generates what IPlytics calls the undeclared patent landscape (the predicted-SEP layer) which is then combined with declared SEPs to form the complete package.
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\nDefine the scope — The target standard is analysed to extract its key technical features and corresponding keywords, forming the basis of what the package should and should not include.
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\nBuild a training set — A set of known relevant patents (positive examples) is assembled, typically from declared SEPs, litigation outcomes, or other public sources, alongside a set of clearly irrelevant patents (negative examples). Together these train the classifier.
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\nTrain the AI classifier — IPlytics' supervised machine learning algorithm (powered by PatentSight+ Classification) learns to distinguish relevant from irrelevant patents across the global patent database, assigning each patent a relevance score.
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\nLLM-based relevance ranking and feature review — LLMs rank candidate patents by relevance using title, abstract, and claims, and verify that all key technical features of the standard are represented in the training set.
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\nManual verification by patent analysts — Expert analysts review the classifier output, remove noise (false positives), confirm coverage across key assignees and technology classifications, and benchmark against known declared SEP pools.
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\nRecall verification and refinement — The landscape is assessed for recall (whether important patents are missing). Low-confidence results are reviewed and the classifier refined if recall rates aren't acceptable.
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\nFeature tagging — Each patent family is tagged with specific standard features (e.g., device vs. controller, different standard generations). These tags become filters in the IPlytics platform, enabling precise segmentation for licensing and outreach.
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\nCustomer feedback and final validation — Patent portfolios from representative customers are checked against the landscape. Any gaps, false positives, or mis-tags are corrected before the package is finalised and published on the platform.
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The Undeclared Patent Landscape, Explained
The undeclared patent landscape is the output of the classifier process described above; the predicted-SEP layer of a technology package. It represents the set of patents identified through IPlytics' classification methodology as likely essential to a standard, even though they have not been formally declared to a standards body.
When you access a technology package in IPlytics, you're viewing a pre-built, expert-curated landscape that already combines:
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Declared SEPs from standards development organizations
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Undeclared patents identified through IPlytics' classification methodology
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Analyst validation and quality review
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You don't need to run the classifier yourself as that work is already done, and the results are ready for immediate use.
For technology areas not yet covered by a pre-built package, a custom classification project can be used to identify and validate undeclared patents for the target standard, following the same eight-step process described above.
Available Technology Packages
IPlytics currently provides pre-built technology packages for the following standards:
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Technology Area
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Standards Covered
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Video
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AVC, HEVC, VVC, AV1, VP9
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Audio
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AAC, OPUS, MPEG-H 3D
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Cellular
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2G, 3G, 4G, 5G
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Wi-Fi
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Wi-Fi 4, 5, 6, 7
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Wireless Charging
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Qi1, Qi2
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Cellular IoT
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NB-IoT, LTE-M, LTE-Cat 1, V2X, EVS, IVAS
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Each of these areas has a dedicated knowledge base article describing the specific technology, the standards it encompasses, and what the IPlytics package contains. See Related Articles below.
Why Technology Packages Matter
Without a technology package, a user would need to define search queries, identify training data, run classifiers, and verify results which is a process that typically takes weeks and requires deep domain expertise. Technology packages remove that barrier so users can move straight into analysis.
With a technology package, users can:
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\nStart immediately — access a ready-to-use patent landscape with no setup required.
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\nTrust the coverage — packages are built using a verified, multi-stage methodology with human analyst oversight and customer feedback loops.
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\nGain comprehensive coverage — view declared SEPs alongside undeclared patents in a single, unified view, so no relevant patents are missed.
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\nSegment precisely — use feature tags to filter by standard generation, implementation type, and other dimensions relevant to licensing or litigation.
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\nSupport a range of use cases, including:
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Licensing analysis — evaluating patent ownership and identifying potential licensors or licensees
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Portfolio benchmarking — comparing portfolio strength and size across companies
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Royalty modelling — assessing potential royalty exposure within a technology ecosystem
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Standard compliance assessment — understanding the patent landscape tied to implementing a standard
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Partner and target identification — identifying licensing partners, acquisition targets, or strategic collaborators
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Competitive intelligence — monitoring competitor investment and innovation within a technology area
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How To Request Access
Please note that technology packages are not included in every standard platform subscription and must be confirmed separately.To request access, contact your IPlytics account manager or reach out to the IPlytics team here. Your account manager will confirm eligibility and arrange access.
How to Search Technology Contributions and View Contribution Weight
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What this article covers
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Introduces IP data products from LexisNexis, and the IP datasets available for in-house analytics and research, and how you can use these datasets.
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Highlights the key data offerings, including LexisNexis® IP DataDirect, LexisNexis® PatentSight+™ Bulk Data, LexisNexis® Global Patent Litigation Data, and the LexisNexis PatentAdvisor® API, with links for further information.
Data products from LexisNexis® Intellectual Property Solutions give you direct access to high-quality intellectual property datasets for in-house analytics, research, and strategic decisions. These datasets enable you to integrate structured IP data directly into your own tools, platforms, and workflows.
Whether you are an IP or R&D professional, part of a legal or compliance team, a financial analyst, or a member of an enterprise data and analytics team, these data products help you uncover insights from global patent and litigation data to support a wide range of business and research needs.
These data products support use cases such as patent search and analysis, portfolio benchmarking, technology trend monitoring, litigation monitoring, market intelligence, and portfolio valuation.
This article introduces the Data Products currently available, explains the types of insights they support, outlines how they can be delivered and integrated into your environment, and links to detailed help articles where you can learn more about each dataset.
Available data products
Below is a summary of the key data products currently available.
Provides document-level global patent data, including bibliographic information, legal status, citations, and procedural metadata across 109 patent authorities, with full-text coverage from 70 jurisdictions.
Patent family–level analytics dataset with portfolio metrics and technology landscape data, designed for in-house analytics, business intelligence systems, and strategic decision-making.
A structured dataset containing global patent litigation data of over 600,000 patent-related cases from 45 sources across 20+ jurisdictions, organised by case, party, and patent.
USPTO prosecution dataset covering 10.5+ million US patent applications since 2001, with examiner behavior analytics and predictive metrics, enabling organisations to analyse examiner behaviour and prosecution trends.
Data products from LexisNexis provide structured, high-quality datasets that can be integrated directly into internal tools, analytics platforms, or data pipelines.
These datasets enable you to build your own analytics, automate research workflows, and uncover insights from global intellectual property data.
Common use cases include:
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Patent search and analysis
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Portfolio benchmarking and valuation
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Technology trend monitoring
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ESG and innovation insights
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Litigation monitoring and legal strategy analysis
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Licensing, freedom-to-operate (FTO), and due diligence
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Market intelligence and competitive analysis
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These data products are commonly used by:
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IP and R&D professionals
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Legal and compliance teams
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Financial analysts
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Enterprise data and analytics teams
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How to get started
If you're interested in accessing one of our data products, or want help determining which dataset is right for your use case, our team can help.
It is possible to import patent number to IPlytics. When you are in the patent or SEP database, change one line in your Query Builder to Publication number, then click the import icon on the right side.
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When you click the import icon, the import dialog window will appear and you have two options to import. Either paste your numbers into the left hand field, or import a csv or txt file:
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In the next window, you then will see how many valid numbers were found. Then click at Import in the right bottom corner:
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Short demonstration of the main functionality on IPlytics Platform. Find out how to search, analyze, work with graphs, filter data, customize table and more:
\n \n IPlytics Analysis and Search Queries This brochure is a guide for using IPlytics\n Platform and provides examples on how to analyze and search patents, declared\n SEPs, patent pools, standards documents and standards contributions.IPlytics\n Analysis and Search Queries This brochure is a guide for using IPlytics Platform\n and provides examples on how to analyze and search patents, declared SEPs,\n patent pools, standards documents and standards contributions.\n
IPlytics Analysis and Search Queries PDF Guide
Below is a PDF guide for using IPlytics Platform and provides examples on how to analyze and search patents, declared SEPs, patent pools, standards documents and standards contributions:
Exporting data from the IPlytics Platform is a crucial feature that enhances the usability and flexibility of the platform's analytics and search capabilities. This functionality allows users to save and share insights derived from their analyses, facilitating further examination and collaboration.
Exporting Graphs
In the Analytics section, users can export each graph, enabling them to capture visual representations of data trends and patterns. This is particularly useful for presentations, reports, or any scenario where visual data interpretation is required. By exporting graphs or data, users can seamlessly integrate these visuals into their documentation, ensuring that their findings are communicated effectively.
The analytic sections allows you to export the data of the graph, or to save the image:
Export Results Tables
Similarly, the Search Data view offers the ability to export result tables. This feature allows users to save detailed tables based on the specific information they have selected.
The platform's drag-and-drop functionality enables users to customize the fields included in the export table, ensuring that the exported data aligns with their research needs. Users can name their files and choose to save them in either Excel or CSV format, providing flexibility in how the data is utilized and shared.
In the 'Export Table' feature, you can select the columns of your choice:
Exporting Guidelines
We advise users to export the smallest data set possible in order to ensure that the export is successful, as exporting very large data sets has the potential, on occasion, to fail.
We advise smaller data sets, or larger exports broken down into smaller pieces during the export process. For further assistance, please contact support@lexisnexisip.com.
Export tips and tricks:
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Ideally the export should happen on SEP level, or even better, at document level. We also advise to avoid exporting SEPs at a family level.
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Split large fields across multiple exports
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If SEP Family Level is required, exporting only short/medium text fields at once (see notes below)
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Summary
The export feature is designed to support a wide range of use cases, from detailed data analysis to high-level reporting. By allowing users to export both graphical and tabular data, the IPlytics Platform ensures that users can effectively leverage the insights gained from their research, whether for internal analysis, stakeholder presentations, or collaborative projects. This capability highlights the platform's commitment to providing comprehensive tools for navigating the complex landscape of patents and standards.
Saved queries on the IPlytics Platform are a valuable feature that enhances the efficiency and effectiveness of patent and standards research. This functionality enables users to save and manage their search queries, allowing them to efficiently revisit and execute complex searches without having to rebuild them from the beginning. By saving queries, users can optimize their workflow, ensuring that they can consistently access the most relevant data for their ongoing projects and analyses.
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How to save a search/query
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The process of saving a query is straightforward. Once a user has constructed a search query using the platform's query builder, they can choose to save it for future use. This is particularly beneficial for users who frequently conduct similar searches or need to monitor specific patent landscapes over time. By saving these queries, users can ensure consistency in their research approach and easily track changes or updates in the data. For saving a query you can click on the save button next to the search button.
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In the next step you can select a name for your saved query:
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How to locate your previously saved 'Query'
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The saved query will be displayed in the “my queries” section on the homepage view:
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How to load/manage your saved query from within a search
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Furthermore, you can access and manage your saved queries in the query builder view, by clicking on the “Load” button:
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Simply click the name of the query to load it:
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Summary
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Saved queries can be organized and managed within the platform, allowing users to categorize them based on different projects, technologies, or research objectives. This organization helps users maintain a clear overview of their research activities and ensures that they can quickly locate and execute the queries they need.
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Overall, the saved queries feature on the IPlytics Platform is an essential tool for researchers and analysts who require efficient and reliable access to complex patent and standards data. By enabling users to store, manage, and share their search queries, the platform enhances research practices and empowers users to make informed decisions based on comprehensive and current information.
The search history feature on the IPlytics Platform, in the 'Latest Queries' section on the home page, is a valuable tool that enhances the user experience by providing easy access to recent search queries. This functionality is designed to streamline the research process, allowing users to quickly revisit and execute their most recent searches without the need to reconstruct them from scratch. By saving the latest search queries, the platform ensures that users can maintain continuity in their research efforts and efficiently track changes or updates in the data.
Accessing the search history is straightforward, with the platform providing dedicated sections where users can view their recent queries. This feature is particularly beneficial for users who conduct frequent searches or need to monitor specific patent landscapes over time. By having quick access to their search history, users can ensure consistency in their research approach and easily pick up where they left off. The search history on the IPlytics Platform is stored for one month.
Where can I see recent searches?
There are two areas where you can access your search history.
First, your search history will be displayed on the homepage tab under the “Latest Queries”:
Second, you can access the search history in the query builder using the “History” button:
In the search history overview, you can execute the latest search queries or delete the search by clicking on the query line, like those shown below:
How long is the search history saved for?
The search history will be saved for one month.
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Navigating the home page of the IPlytics Platform is the first step towards unlocking the full potential for patent and standards analysis. The home page is designed to provide users with a seamless and intuitive experience, offering easy access to the platform's features and databases. Upon logging in, users are greeted with a clean and organized interface that highlights the key functionalities available.
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How to navigate the Home Page
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At the top of the home page, the main navigation bar allows users to quickly access different sections of the platform, including accessing the default homepage, the search section, including patents, SEPs, standards, and the dashboard hub.
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This layout ensures that users can effortlessly switch between different types of data and analysis tools, depending on their specific needs.
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The default home page includes the following overview:
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“My Queries” box – which displays your saved queries.
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“Search, Create & Analyze” box – which allows you to access the dashboard hub, the SEP database or the standard database.
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“Latest Queries” box – which indicates your latest executed searches.
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Help and Support
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The “Help and Support section” can be found in the drop down menu in the top right of your Home Page.
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The help and support section includes quick links to tutorials, user guides, and support resources and frequently asked questions, ensuring that users have access to the assistance they need to maximize their use of the platform.
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What is the Analytics view and where can I find it?
The Analytics view on the IPlytics Platform is a dynamic feature that provides users with a visual representation of data, enabling them to gain insights into patents, declared SEPs, and standards contributions through various graphical formats. This view is designed to facilitate a deeper understanding of complex data sets by transforming them into intuitive and interactive visualizations. It is available below the Query Builder, once you've constructed a search:
Exploring the Data
Upon accessing the Analytics view, users are presented with a range of graph options that allow them to explore data from different perspectives. These graphs are customizable, enabling users to select specific data points, time frames, and other parameters to tailor the visualizations to their specific needs.
You can choose options for visualizations between:
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Declarations View
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SEP’s view
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Families view
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With the Export options, you can choose between:
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Export Data
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Save Image
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1. Market Overview Graph:
This default graph provides a snapshot of the largest patent portfolio owners within your search results. It ranks the top 10 companies based on their patent share and displays the market overview graph where the patent share is on the y-axis and the technical relevance is on the x-axis. The bubble size will indicate the market coverage. You are also able to select different settings for each axis or the bubble indication like the semantic essentiality score, team size, or other IPlytics indicators. You are also able to select other companies from the analytics table by selecting or deselecting companies by clicking on their name. Additionally, you have the option to use the filter of Ultimate Owner, Current Assignee, Applicant and Declaring Company
If you want to highlight a company, you can hoover over the bubble and select Highlight
2. Over Time Graph:
This graph displays trends in patent filings, declarations, or contributions over a specified period. It helps users identify patterns and shifts in technological development, providing valuable insights into industry dynamics and innovation cycles. The user can select companies and set different graph characteristics.
You are also able to select all companies to investigate the patent or standard contribution trend of all companies.
With the Time Bar underneath, you can set to your preference in what you want to visualize.
3. Industry Trend Graph:
This visualization highlights trends within specific industry sectors or fields, allowing users to understand how different technologies are evolving and which sectors are experiencing growth or decline.
4. Authority Graph:
This graph provides a geographical representation of patent filings or contributions, showing the distribution of activity across different authorities. It is particularly useful for identifying key markets and understanding regional variations in technological development. You are able to select three different graphs in the graph settings.
Bar Chart
World Map
Table Chart
5. Indicators Radar Graph:
This graph offers a multi-dimensional view of various IPlytics indicators, such as Market Coverage, SES score, Technical Relevance or Radicalness. It provides a comprehensive overview of varied factors influencing the patent strengths of the selected companies. You can choose the following visualizations.
Radar Chart
Table
6. Rank Graph:
The rank graph explores the ranking of companies based on the active and inactive number of patent families. You have the following options to apply for the Rank Bart Chart.
Active
\nKind Type In this view, you can see the patent application, granted patent and divisional:
7. Industry Clusters
The industry cluster shows the share of all patents from the result list to the dedicated industry clusters.
8. IPC/CPC Portfolio Concentration
The IPC/CPC Portfolio Concentration graph shows the IPC/CPC Portfolio Concentration of the selected companies.
When you hoover over a bubble the IPlytics platform allows you to view the data
9. Citation
The citation graph shows the citations of the portfolio of the selected company.
Under the Citations icon
Here, you can select the citation direction of:
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Citing
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Cited
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Citing and Cited
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When you select the smaller bubble, you see the Company Name or Ultimate Owner, the citation direction, the citation of the Ultimate Owner, how many citations, and the option to view the patent families.
10. Co-Assignee
The Co-Assignee graph shows the co-assignees of the patent portfolio of the selected company.
In the Analytics view, you have the option to visualize the number of patent families companies are collaborating with each other. When you hoover with your mouse on the smaller bubble, you see the following:
Here, you can make a drill down to view the patent families.
11. Litigation
The litigation graph shows the litigation information of the patent portfolio of the selected company.
Under the litigations icon you have the possibility to the litigation direction of:
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Litigating
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Litigated
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Litigating and litigated
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When you select the smaller bubble between companies, you can see the following: the name of the company, the litigation direction, the name of the company of ligation, how many patent families, and how many cases.
Additionally, you have the option to view the families
12. Transferred
The transferred graph shows the patent transferred information of the patent portfolio of the selected company.
When you select the smaller bubble, you see additional insight into the company name and to who the new owner is of the patent, how many families, and the option to view the families.
The Analytics view on the IPlytics Platform is an essential tool for users seeking to visualize and interpret complex data sets. By offering a range of customizable graphs, it empowers users to uncover trends, identify key players, and make informed decisions based on a comprehensive understanding of the patent and standards landscape. Whether for strategic planning, competitive analysis, or innovation management, the Analytics view provides the insights needed to navigate the ever-evolving world of technology and intellectual property.
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AI Classifiers allow you to zone in on the patents that are relevant to the technology areas you operate in by building a 'Classifier' that is defined to your technology area.
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At its core, an AI Classifier is a supervised machine learning algorithm trained to recognize patent families relevant to a specific technology domain. Each patent family receives a classifier score ranging from 0 to 1 — where 0 means no relevance, and 1 signals a strong match. Everything above a 0.5 score, is deemed a positive match to the classifier technology domain. LexisNexis PatentSight+ uses AI Classifiers to read all the millions of patents globally, to pull the relevant patents into your Classifier.
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This scoring system enables precise, focused analysis of patent portfolios, technology landscapes, and innovation trends. By filtering based on classifier scores, users can quickly hone in on the most relevant inventions, streamline competitive intelligence, and make data-driven decisions with greater confidence.
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We can assist you in the building of the AI Classifiers, or you can be trained to build them yourself. We find a solution that fits your requirements.
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The Classifier is defined by you and the machine does all the hard work of going and finding the right patents. The AI Classifier in PatentSight+ transforms how users explore and analyze patent data by introducing classifier-based filtering and insights. The machine can read more than 60 million patents an hour and looks at 200,000 data points in the patent.
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Benefits of AI Classifiers in PatentSight
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AI Classifiers in PatentSight gives you accurate and up-to-date patent information on how you view the technology spaces you are operating in. You can build a custom taxonomy of AI Classifiers relevant to your business needs, allowing you to make better decisions about your portfolio.
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Analyse your custom taxonomy in more detail with the powerful PatentSight features available – Patent Asset Index metrics, captivating visualizations, unparalleled flexibility, and superior data quality. Whether your analyses is for competitive intelligence, benchmarking, trend scouting, or portfolio optimization, AI Classification allows for these analyses in the technology space relevant to you.
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Patent portfolios are strategic assets for your organization, and managing them to achieve your business objective requires accurate customized information that is easy to access.
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Synchronization of AI Classifiers into PatentSight
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To build AI Classifiers, a subscription to LexisNexis Classification is required. This subscription provides access to the necessary tools and resources for creating AI Classifiers. If you're interested in learning more about classifier building or need assistance, please reach out to your Customer Success Manager or contact support@lexisnexisIP.com so we can provide detailed information and guidance, tailored to your needs.
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The synchronization of AI Classifiers into PatentSight+ follows specific rules to ensure that relevant patent families are accurately exported, so that you can then review these in various different reports and analyses. Here's how this works:
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When AI Classifiers are built, positive and negative patent families are used to train the algorithm as to what should be included in the results (positive patent examples) and excluded from the results (negative patent examples). Once built, the AI Classifiers sit in your account and can be used repeatedly to generate patent searches and analyses for those technology areas.
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When running the AI Classifier against a set of patent families, each patent family receives a classifier score ranging from 0 to 1 — where 0 means no relevance, and 1 signals a strong match.
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When generating a search utilizing AI Classifiers in PatentSight+, only those patent families with a score above 0.5, are deemed a positive match to the classifier technology domain, and are included in the results. This threshold ensures that only patents with a moderate to high confidence level of relevance are included, optimizing the quality and focus of the analysis.
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Please note that Patent families that were part of the positive training set for the AI Classifier, are also deemed to be relevant to the classifier technology domain, regardless of their score. These patent are also exported to PatentSight+, and would be included to any search query where that Classifier is applied.
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Enquire to find out more...
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If you have any questions about the new capabilities, please reach out to your customer success manager, who will be happy to help you, or send us a note at support@lexisnexisip.com. Further information can also be found on the following links:
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PatentSight+ is revolutionizing the way you perform intellectual property (IP) analysis by combining intuitive user inputs with advanced artificial intelligence. This article explains the cutting-edge AI features that empower you to generate insightful analysis quickly and accurately.
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What are the AI Powered features in PatentSight+?
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PatentSight+ leverages AI in both the Analysis Builder, and the automated generation of Insights. Describe your IP analysis needs and let AI instantly generate the right charts and tables, and analysis insights.
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AI-Powered Analysis Builder
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The AI-Powered Analysis Builder allows you to search for an owner, and provide a description for how you want to analyze that owner's patent portfolio. The AI-Powered Analysis builder then suggests analysis templates to build out your analysis.
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• Streamline Your Analysis Process: Begin by describing your specific IP analysis goals. The AI-driven interface guides you through setting up your search, and suggesting the type of output you'd like to include in your analysis:
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• Simplify Complex Data Navigation: The analysis builder distills large volumes of patent data into clear, actionable insights, helping you navigate the often complex landscape of IP information effortlessly.
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• Creates Visual Insights Instantly: Based on the completed query, the system generates objective insights in the form of charts and tables, saving you the time and effort required to create visual data representations manually.
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AI-Powered Insights
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The AI-Powered Insights feature automatically converts the chart data from your search into detailed descriptions, generated by AI, conveniently shown in a side panel. Quickly understand your chart and gain additional insights that go beyond patent data, providing a comprehensive context for your chart's finding.
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The AI analyzes the search data when using the Analysis Builder, and not only automatically generates relevant charts and tables linked to your analysis goals, but also generates AI-Powered Insights that help you to understand trends, compare competitors, and inform strategic decisions. These insights are tailored to your analysis goals as outlined in the Analysis Builder. The Insights consists of a Summary, Key Insights, and Next Steps for your analysis.
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How do they work?
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After selecting or generating your search, this information is fed to the Large Language Model (LLM) which processes the contextual chart data, and search details, which the LLM then uses to generate the explanation.
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The AI Assistant then quickly generates a 'Summary', setting the context and highlighting key chart statements.
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The 'Key Insights' section presents the main insights and potential drivers of the output and sources, while the 'Next Steps' section offers further analysis suggestions or business action recommendations based on these insights. Here is a brief interpretation of the data:
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Analysis Builder Walk Through
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Search for a patent owner
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From the home page, the Analysis Builder can be found at the top. There are two fields. The first allows for the input of a patent owner's portfolio. Simply input the name of any patent owner that you'd like to analyse. Input the name and select from the drop down list.
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Describe your analysis goal
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Next input your analysis goal to the next field. When you click into the field, the builder makes suggestions for instructions that can be input. See below:
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These instructions are then matched to an analysis template, which is a selection of charts and tables that fit in with the analysis goal that has been input.
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Insights Walk Through
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When generating a search from the analysis builder, the AI-Powered Insights feature automatically converts the chart data from your search into detailed descriptions, generated by AI, conveniently shown in the side panel. These insights are split into a Summary, Key Findings and Next Steps.
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These Insights are not only linked to the Organisation that you've input to the Analysis builder, but also the analysis goal that you input too. The goal of these AI Powered Insights is to inspire you, to bring up information for consideration that you may not have originally considered, or to simply cross check your understanding. You will also find the option to create a more generic version of the AI Insights without the context of your analysis goal, which can be found at the bottom of the side panel:
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Insights from a Custom Analysis
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AI Powered Insights can also be generated from within a Custom Analysis:
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The only difference being that you are required to click the 'Generate Insights' button from within your desired chart. The summary, key insights and next steps will then be displayed on the right.
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Handy Hint: When generating insights from a custom analysis, those insights will not be linked to the goal of the analysis as the AI powered insights does not know your intention. Instead, the key insights will be based on the search input and chart selection/data.
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Use Cases
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PatentSight's AI-Powered Analysis Builder and AI-Powered Insights not only streamline your analysis process but also inspire insightful outcomes. In this section, we aim to inspire your use of these tools and show you what's possible to get you started. If you wish to discuss these AI powered use cases in more detail, please do reach out to support@lexisnexisip.com.
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By Business Case:
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Quickly Understand a Company's Patent Strategy
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'Show me Company X's patent strength and innovation trends'
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Suggests charts like: Patent Asset Index Trend, Quality Trend, Technology Clusters: Patent Asset Index Trend\n
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Offers a pre-filled workbook showing portfolio quality, technologies, and trends
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Why It Matters:
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Helps non-experts get executive-ready insights in seconds,
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Supports strategy, M&A scouting, and competitive response.
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Evaluate the Geographic footprint of a Patent Portfolio
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'Where is Company X protecting it's IP?
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Auto-selects charts such as: International Protection Strategies, Active Authorities, Active In: Patent Asset Index Trend, Active In: Portfolio Size Trend\n
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Why It Matters:
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Supports freedom-to-operate risk assessments, market entry strategies, and IP enforcement planning,
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Especially useful for legal teams and regional product heads.
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Identify and Reduce Patent Maintenance Costs
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“Which of our patents could be pruned to save costs?”
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Suggests charts like: Annuity Fees Saving Potential, External vs. Internal Technology Relevance, Filing Year: Legal Status, Value Distribution, International Protection Strategies\n
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Why It Matters:
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Helps IP teams to a) spot low-value or non-strategic patents that are costly to maintain, b) prioritise patent pruning candidates, c) focus budget on high-value or high-risk assets,
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Enables data-driven portfolio rationalisation for leaner IP operations.
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Identify Key Inventors and Innovation Hubs
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'Who are the top inventors at Company X?'
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Suggests charts like: Inventor: Patent Asset Index Ranking, Inventor: Patent Asset Index Trend, Inventor: Portfolio Size Trend, Inventor: Quality vs. Quantity\n
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Why It Matters:
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Helps identify R&D talent clusters, supports M&A or hiring due diligence, and highlights centres of technical excellence,
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Valuable for organisational benchmarking and strategic HR use cases.
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By Use Case:
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Citation Analysis - Who is building on the technology of Company X?
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Licensing - What are the licensing opportunities for Company X? For Company X, how can i monetise this portfolio?
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Owner Profile - Show me Company X's strongest and most highly cited patent?
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R&D Strategy - Where are Company X's R&D centres located?
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Portfolio Management - Which technologies and IPCs make up the portfolio?
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FAQs
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Is my data safe when using AI-Powered features?
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Yes, all AI interactions are processed through a private OpenAI service hosted in Microsoft Azure and provisioned exclusively by LexisNexis IP. Your inputs and outputs are:
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Not shared with other customers;
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Not accessible to OpenAI for training or improvement;
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Not used to improve third-party models or services.
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Do these features come at an extra cost?
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No, AI-Powered Insights and AI-Powered Analysis Builder are included at no additional charge.
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What languages do the features support? \n
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Both features currently provide the best results with English input and output.
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Which AI model do these features use?
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Large Language Models from OpenAI, to be precise currently GPT-4o is used. Models will be updated as needed for optimal performance.
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Can I trust the AI-Powered Insights?
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Mostly. Internal and beta testing shows 75% of chart insights are free from all types of accuracy issues. As with any AI output, human validation is recommended, especially for critical decisions.
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Can I interact with or customize the AI-Powered Insights?
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No, not at this stage. Interactivity is planned for future updates. Users can submit feedback to help improve relevance and focus areas.
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Can I compare Insights across time or previous analyses?
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No, not currently. The feature does not store previous insights for comparison.
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What makes the AI-Powered Analysis Builder unique?
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It enables you to express your analytical goal in plain English and instantly receive suggested charts, tables, and narrative insights - tailored to your intent. This significantly lowers the entrance barrier for users - especially occasional and new users.
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How good are the auto-suggested charts and tables within Analysis Builder?
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Suggestions are based on your natural language input. Some input work better than others. On average suggestions are 70-75% spot on. Quality is measured by a) precision-recall evaluation and b) qualitative feedback from subject matter experts.
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Does it work with multiple owners or filters like UN SDGs?
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No, not yet. The current release supports building an analysis for one owner - at a time. One owner analytics is the most popular use case in PatentSight+.
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Welcome to the LexisNexis® Intellectual Property Solutions On-Demand Training Academy
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This article provides an introduction to the continuous enhancements to our On-Demand Training Platform. To register and start exploring the current learning content, please visit our:
Develop your knowledge and enhance your reporting capabilities
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Withour On-Demand training platform, our objective is to ensure you can develop your knowledge of the platforms that we offer, at a time that's convenient to you and at a pace that suits you. Elevate your experience in three product areas, all with the aim to enhance your navigation and reporting capabilities:
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Introduction to Patents - This stand alone course provides an introduction to patents for anyone unfamiliar with Intellectual Property, or for anyone looking to understand more about why 'IP' is important, and how it provides a window into the direction that Organisations or technologies are taking.
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PatentSight - These learning paths and courses are designed to introduce PatentSight Basic concepts and data, including how we organize and present that data, before introducing the interface, how to navigate the platform, how to search, and review the results. This is an all encompassing overview of the data we use, right through to generating a basic search and general workbook settings.
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Classification - These learning paths and courses are designed to introduce Classification terminology and features, including technology grouping options and report types relevant to your workflows and analysis. The Classifier Building learning path also teaches you how to build AI and Machine Learning Classifiers to identify all relevant patents related to your technology definitions.
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The On-Demand Training academy can be accessed here. You will be asked to sign up for an account prior to entry.
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Become Accredited in LexisNexis IP Products
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You may choose to become certified in our individual solutions where you'll receive accreditation, that can be posted to your LinkedIn:
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Alternatively you may wish to access individual courses via the Full Course Catalog:
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Each Course consists of multiple lessons, which can be undertaken at a pace convenient to you. The lessons are in video format of varying length which is clearly listed, and dependent on the subject or content that is being covered. You can easily return to where you left off, when returning to the platform. You'll be asked to log in with your email and password that you set on first log in.
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For any access issues, please contact support@lexisnexisip.com or your Customer Success Manager for more information.
Access the patent family tree in the Family Viewer of the Result List to visualize the relationships between patent applications. To explore all key features, you can open the tree in full-screen view.
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Key Features
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ExploreFamily Structures Visualize relationships between applications, publications, and grants in chronological order, starting from the earliest priority application.
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Identify Filing Types Spot provisional, continuation, and divisional applications to trace the development of each patent family.
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View Patent Information See information such as application and publication dates, along with the legal status of each family member.
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UnderstandFiling Strategies Track the order of national, EP, UP, or PCT applications to reveal each family’s filing strategy.
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Share LinkorExport Image Copyits unique link to share the family tree or export it as an image for use in presentations and other files.
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See our detailedhelp article for more information.
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Improvement: Classification Now Accessible from the Welcome Page
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If you are building custom classifiers, you can now access the Classification building interface directly from the PatentSight+ welcome page.
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The Classification interface has been redesigned to match the visual style of the main application giving you a more consistent experience.
Improvement: Email Notifications for Shared Objects
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When you share an object with another user, you can now choose to notify them by email. You also have the option to include a custom message for added context.
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In addition, the sharing settings are now in a separate tab, providing more space for easier sharing.
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For convenient access, the sharing notification email includes a link to the shared object.
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You can opt out of email notifications for all objects or for specific ones at any time by turning them off in the new “Notifications” tab in your account settings.
This update improves clustering accuracy, coverage, and title selection. Technology clusters offer an AI-driven, unbiased view on competitors' patent portfolios, for more precise technology classification and enhanced competitive intelligence.
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Improvement: Updated Annuity Fees
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Updated annuity fee values are now available for the following authorities:
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AU, BG. CA, CH, CZ, DE, DK, EP, ES, FI, FR, HK, HR, JP, KR, NL, NO, PL, PT, RO, RU, SE, SG, TR, TW.
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These updated values, along with the related attributes and measures, allow you to calculate future renewal costs for maintaining patent portfolios.
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The next annuity fees update is planned for January 2025 for US and CA.
You can now easily share your currently open workbook using the new “Share” option in the “Workbook” menu. This option is enabled once the workbook is saved and if you have the necessary sharing permissions.
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TechDiscovery allows you to quickly get to the list of the most relevant patent families for your patent research or analysis and easily refine these if necessary. Skip the search part, and get straight to the data and analysis you require.
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You can use either patent numbers, family representative patent numbers or text, to begin a search. The text can be either a simple description of the technology, longer form technical information (e.g. your own unpublished patents), or even product descriptions/patent paragraphs from competitors. You can also use a combination of both patent examples and text (where possible).
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How it can help you
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If you want to quickly explore a patent landscape for a specific technology space or look for patents that are similar to your examples, TechDiscovery is the right tool for you. Similarly, if you’d like to quickly retrieve a set of relevant patents to better understand the latest innovations in your research field, but you’re not sure where to start, Tech Discovery can help you to start your search.
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The purpose of this type of search is to find a set of relevant patents to the technology or invention. These patents can then be useful for starting the patent research (for R&D or legal purposes) or as a first step of the patent analysis, to quickly and easily evaluate the largest players and trends within a tech space for example.
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You may be a patent search expert wanting to verify your search query and results, or to identify potentially missed concepts or patents using TechDiscovery. You can then sort by most relevant results using the similarity score.
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Alternatively, you may be an Innovator or R&D engineer looking for a way to start your search as a non- search expert. TechDiscovery can be used to easily find patents in your technology area by simply inputting a short piece of text or an example patent.
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TechDiscovery can be used to:
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Conduct a Knock out search to quickly identify potential Prior Art. Have a quick and inspirational start for your Patentability Search, Freedom to Operate Search, or your Invalidity Search.
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Quickly explore a tech area to see what patents currently exist within the space, to explore current competitors or collaborators.
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Perhaps you know very little about the technology area and you want to understand who the innovators are in that area. TechDiscovery doesn’t just give you an easy starting point, but it also inspires your research and may support you to uncover what “you don’t already know”.
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You may have a lot of wide ranging questions from the business that you want to answer quickly. Tech explorer allows you to quickly explore a technology area with as little as one word.
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You may want to look for patents that are similar to examples that you already have. Using generative AI and cyphers machine learning algorithm to vectorize patents tech explorer is able to bring back similar patents to the technology area.
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Get to a list of the most relevant patent families for your analysis, refine these, and get straight to the data and analysis you require within minutes.
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How does TechDiscovery work?
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Similarity searching starts with vectorising every patent family in the universe (think of this like giving each patent family a unique fingerprint). Each patent family can then have its vector (fingerprint) compared against others to identify vectors (patent families) that is closest to it, returning the closest results based on the chosen sample size (50, 100, 1000 etc.). The product's deep learning model (“algorithm”) is specifically designed for patent linguistic tasks and uses the patent title, abstract and claims to generate a vector for each individual patent family. The product uses generative AI to assist the vectorisation (or fingerprinting) of information when you have very little information e.g. a technology name or brief description.
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How does TechDiscovery differ from Semantic Search?
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Here are the key differences to semantic searching/boolean searching in TechDiscovery:
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The results are much better (more relevant results, more results found).
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You can search based on patent numbers.
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You can use whole paragraphs of text.
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The search is specific to patent text, not 'general text similarity'.
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You can combine multiple inputs into one search for example, patents, blocks of text, and technology names.
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LexisNexis® Classification has a fresh new look and many small improvements. We'd like to introduce the new design, and reassure you that it's the same product you know and love, with some cosmetic and feature enhancements to streamline your experience. Explore the changes here.
New Layout
We've rolled out a new design of the homepage which removes the need for separate tiles for the report wizard, Classifier Landscape report builder and UTT Landscape report builder. These have been removed from the dashboard and have been replaced with one central location for all of your reporting needs:
Tech Explorer becomes TechDiscovery
Tech Explorer is now known as TechDiscovery. We will continue to improve this feature under it's new name:
New Patent Family View
Now when you click into the Patent Family View from the report dashboard, and select to review a patent family in more detail, you now have the list view still available to you on the left. We hope that this will streamline your experience when reviewing the patent family list:
New Report Dashboard and View
Now when you click into a chart or dataset from the report dashboard or selected chart list, the various chart display options are shown to the left, and the chart list is displayed to the right improving the way in which you can navigate:
We hope you enjoy the new Classification layout. Please do share your feedback via the dedicated feedback section in the platform here:
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Need help? Request support and we’ll connect you with a Classification expert.
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