Unlocking Insights: A Human-Expertise-Driven EoU Analysis with XLSCOUT

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Overview

A USA-headquartered, global semiconductors and chipsets manufacturing corporation with an active patent portfolio of thousands of patent assets, some of which are designated as core patents for their respective technology areas.

Challenges and Objectives

Challenges
  • Reviewing a large dataset is time-consuming and resource intensive

  • Efficient identification of key patents through AI for manual evaluation

  • AI alone struggles with complex tasks like interpreting figures, chip architectures, and signal flow diagrams

Objectives
  • Efficiently map patents to relevant products

  • Ensure high accuracy and depth of analysis

  • Create claim charts with precise interpretation of product data

Problem Statement 

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Analyze the patent portfolio using AI

Analyze a portfolio of 300+ patents to identify the best potentials for monetization.

Identify Potential Infringers

Identify companies and their products that patents could map to, from a pool of over 100k relevant products.

Analyze the patent portfolio using AI

Prepare claim charts against best matches using AI and validate them with relevant subject matter experts.

Solution: AI + Human Expertise

TTC/XLSCOUT Solutions

TTC teams leveraged XLSCOUT
AI technologies to minimize
manual workload, reducing
the effort needed to pinpoint
the most relevant products to
target and to generate claim
charts to review and refine.

XLSCOUT AI Technology
TTC Human Expertise
Ranked patents against a massive product pool, narrowing focusBridging AI gaps where it struggled (e.g., analyzing diagrams, chip architectures, and datasheets)
Generated AI-powered charts for initial analysis frameworkRefining AI-generated insights for accuracy and completeness

Impact & Results

Optimized Resource Allocation

Experts focused on high-value analysis rather than exhaustive manual reviews

Faster, More Accurate Analysis

AI dramatically reduced the time spent on initial patent-product mapping.

Improved Decision-Making

Human intervention corrected and refined AI results, leading to high-confidence insights.

Quick License Negotiations

The client could enter into new license negotiations quickly.

Conclusion

To sustain and scale the value delivered, the following strategic steps are being continued post-engagement:

  • Deploying AI agents to continuously track new product launches by key targets and automatically map them against the client’s patents.
  • AI agents to consider partially mapped claims and suggest claim modifications supported by patent specifications to get a better read on the products.
  • Analyzing the next set of hundreds of patents to identify new monetization opportunities.
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