Large Patent Portfolio Assessment Using AI

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Overview

A USA headquartered corporation which is a global leader in industrial technologies with an active patent portfolio of over 10,000+ assets spread across multiple technology areas and applications spectrum.

Challenges and Objectives

Challenges
  • Varied patents may read onto a multitude of companies.
  • A large number of patents takes significant time to analyze.
  • Identifying accurate product documentation is difficult.
Objectives
  • Identify the relevant target companies
  • Identify the best patents for licensing
  • Create claim charts for best mappings

Problem Statement 

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Analyze the patent portfolio using AI

Analyze a portfolio of 1000+ 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

Categorizations of Patents
Identification of Targets
Analysis of Patents
Human Validation of AI Output
  • The entire portfolio of patents was categorized into 9 taxonomy categories using AI
  • The categorization helped the users understand the portfolio better and focus on each major category
  • Representative patents from each category were analyzed through XLSCOUT to identify relevant target companies for each set
  • AI identification of targets saved hundreds of hours of human efforts with highly accurate data
  • All the patents were analyzed through Patdigger LLM module of XLSCOUT against the identified target companies
  • Patdigger LLM automatically identified most relevant products individually for each patent and created a map
  • Subject matter experts chose the best patent maps through AI score and reviewed the charts
  • Manual review helped with validating the accuracy of AI’s interpretation and the best charts could be supplemented with additional information
Portfolio Assessment

The entire portfolio was analyzed on Patdigger LLM module of XLSCOUT

Patdigger LLM uses advanced AI technologies to accurately identify the products of target companies that each of the patents could map on to and provides a numerical score of which products are the best matches against each patent.

Our team of subject matter experts reviewed the AI generated charts in detail to validate the findings and augment the charts manually.

Impact & Results

1000+ patents analyzed cost effectively

Analysis and recommendations completed within 3 weeks

Client received numerical data driven actionable insights

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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