Actual intelligence on IP

Who We Are

Patnt.ai is built specifically for IP strategy, valuation, and opportunity analysis, and that's what separates us from most of the IP tools on the market.

Most IP legal-tech platforms are designed for legal workflows: searching prior art, managing prosecution, tracking deadlines, and supporting litigation. They're excellent at that. But they answer a legal question ("what exists, and who owns it?"), not a business one ("what is this worth, where is the opportunity, and how does it stack up against the market?").

We start with the business question, developed out of hands-on IP valuation and commercialization work, where combining patent diligence with commercial and market analysis is the core of the practice. Built by strategists and valuation practitioners, for founders, investors, corporate teams, and the advisors who support them.

Our purpose

Curated commercial analysis

01

Too much IP decision-making runs on patent counts, headline claims, and judgment calls that can't be examined or repeated. We believe the quality of a patent can be measured, and that doing so consistently, transparently, and at scale leads to better decisions: what to file, hold, license, and the value and ROI of a portfolio

Patent strategy and valuation should rest on rigorous, quantitative analysis

A patent is only as valuable as the product and market it addresses

02

Legal strength is necessary but not sufficient. A technically strong patent that doesn't align with a commercial product's actual features, or that sits in a market without meaningful potential for incremental income, may be worth far less than it appears

Our approach

Our tech combines 3 layers

Proprietary scoring

1

Each patent is assessed on a multi-factor framework that draws on prosecution history, claim structure, citation behavior, family and filing patterns, and other signals associated with strength, breadth, and competitive relevance. The methodology is under active development and validation with IP practitioners


AI-assisted analysis

2

Machine learning and language models help interpret claim language, map patents to product features, and cluster technologies at a level of precision that classification codes alone can't reach. Designed to incorporate human expertise at various stages of analysis


Custom landscape visualization

3

Results are presented as patent-to-product matrices and technology maps that show competitive positioning, concentration, and open whitespace at a glance, designed for decision-makers, not just patent professionals

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