Patentvector

What It Does

PatentVector is a patent-analytics platform that scores and ranks patents by influence. It builds an influence-weighted map of the global patent system using network science (eigenvector centrality and graph analysis) and machine learning, covering — by the vendor’s account — more than 150 million patents and applications from over 200 patent authorities. Each patent gets a numeric “PV Score” where 1.0 is the mean, letting users compare the relative importance of patents, portfolios, inventors, companies, examiners and attorneys.

For IP counsel, in-house patent teams and analysts, the tool sits at the research and portfolio-analysis stage: finding the patents that matter in a technology area, valuing a portfolio, or sizing up a competitor’s or an examiner’s record. It is an analytics layer, not a drafting or docketing tool.

What We Found

PatentVector has external recognition: it was named to a Stanford CodeX legal-tech companies list, and its network-building algorithm won the 2016 WSDM Cup. Company-profile databases list it as a small, Seattle-based firm founded in 2013, with no disclosed institutional funding.

What We Haven’t Verified

• Patent-coverage and score figures (150M+ patents, scoring methodology) — vendor-stated, not independently tested.
• Pricing — not published.
• Current team size.

Company Info

• Sector: Legal Tech (patent analytics)
• Founded: 2013
• HQ: Seattle, USA