Welcome to this introduction to LexisNexis Protégé™, a GenAI-powered assistant designed to help users move faster from a business question to patent-based insight.
Protégé is built to interpret natural language questions, identify the underlying analytical need, search LexisNexis® PatentSight+™ data, create charts, summarize findings, and recommend next steps.
The key point is that Protégé is not simply generating an answer from a prompt. It is grounded in real PatentSight+ data: real patent families, real owners, real filing trends, real legal and quality metrics, and real patent content.
- Watch the Video Walkthrough - View the complete 5-minute demonstration.
- Follow the Image-Based Step-by-Step Guide - Use screenshots and written instructions to complete the same process at your own pace.
Video Walkthrough
Image-Based Step-by-Step Guide
Starting from a business question
In this example, imagine an urgent email has arrived.
The email says there are new developments around solid-state battery technology, specifically sulfide-based solid electrolytes designed to improve battery safety, energy density, and fast-charging performance. It also mentions that Toyota may be building a strong position in this area, but it is unclear who else is actively investing and how significant the activity really is.
Instead of asking the user to build a search strategy from scratch, Protégé interprets the email and identifies the analytical intent.
It understands that the user needs a fast technology landscape, competitor context, and evidence that can support an R&D or leadership discussion.
This is to show you that you can simply take the detail of the email, and Protégé understands the requirement for a technology landscape, and additional information just provides more context.
Equally, you could have entered any of the following prompts:
“Create a patent landscape for solid-state battery electrolyte materials with a focus on sulfide-based solid electrolytes. Show the top owners, filing trends, and key insights.”
"Investigate Toyota's activity in solid-state battery electrolyte materials, specifically on sulfide-based solid electrolytes and compare it with our portfolio, 'X Company' and other top patent owners."
How Protégé reasons
After the prompt is submitted, Protégé begins by analyzing the context of the request.
In this example, it identifies two core concepts - Sulfide-based solid electrolyte technologies and the broader solid-state battery landscape.
Protégé then creates a transparent PatentSight+ search strategy using a combination of keywords, patent classifications, and patent metadata to connect these concepts into a focused result set.
This is important because the search remains auditable and reviewable. Users can inspect the strategy, understand what was searched, and validate whether the resulting dataset is relevant to the business question.
Why Boolean search is used
Protégé currently uses Boolean-style search because auditability and traceability are critical in patent analytics.
A human-readable search strategy allows users to review the scope of the analysis, understand why certain patents were included, and validate the relevance of the result set.
Protégé is also evolving toward more advanced AI-assisted search capabilities, while maintaining the same level of transparency and user control expected in professional patent analysis.
Generating the analysis
Once the result set is established, Protégé uses PatentSight data to generate analytical views such as:
- Top patent owners
- Filing trends over time
- Portfolio quality and strength comparisons
- Competitive positioning across the technology space
To strengthen the analysis, Protégé can also review relevant public information and industry signals alongside the patent data. This helps provide additional market context while keeping the core analysis grounded in PatentSight data.
In this solid-state battery example, Protégé identifies where companies like Toyota, Samsung SDI, and Panasonic appear within the sulfide-based electrolyte landscape and how their patent activity compares across the technology space.
If the patent data alone does not fully explain a market signal, Protégé can also use external public information as contextual support, while keeping the patent analysis grounded in PatentSight data.
Summaries and next steps
Protégé then summarizes the findings.
It explains what the charts show, highlights key insights, and suggests possible next steps.
For example, it may recommend narrowing the search, comparing specific competitors, reviewing filing trends, analyzing high-impact patent families, or examining the claims of the most relevant patents.
The user can continue the conversation by asking follow-up questions, such as:
“Focus only on sulfide-based electrolyte materials.”
“Compare Toyota with Samsung SDI and Panasonic.”
“Show the top patent families by Patent Asset Index.”
“Review the claims of the top 10 patent families.”
“Which companies are increasing filing activity most rapidly over the last five years?”
Working with the results
Protégé can transfer a search into PatentSight so that users can continue the analysis there.
Users can also download chart data and download individual charts (Export), or copy the chart image to clipboard
You can also copy the text response for use in an email or report.
Future development plans include deeper integration with PatentSight workbooks, so users can move more directly from Protégé analysis into a shareable workbook environment.
Summary
Protégé helps users move from an unstructured question to a structured patent intelligence answer.
It interprets the question, creates an auditable search, analyzes PatentSight data, generates charts, summarizes insights, and recommends next steps.
It is designed to accelerate analysis while keeping the result grounded, transparent, and reviewable.