Thomas Reichert

Law Professor · Legal AI Advisor · IP Attorney

Thomas Reichert

I use AI to study how the law actually works: large datasets of real decisions, models I fine‑tune myself, and results published in law journals. I help law firms and legal departments bring the same discipline into their own practice.

~4,000 TTAB decisions coded with AI
99.55% Accuracy of two DuPont factors
453 Human-coded checks on the Fair Use Database
USPTO Registered patent attorney

Recent talks Stanford Law School (IP Scholars Conference) · Northwestern Pritzker School of Law · Southeastern Association of Law Schools · Lawyers Association of Kansas City · Jackson County Bar Association CLE All talks →

Coverage of the Research

This paper could be very useful... Empirical support for John Welch's mantra, which turns out to be understated: mark and goods don't predict 95% of the outcomes of 2(d) appeals to the TTAB, they predict 99%!

Rebecca Tushnet, Frank Stanton Professor of the First Amendment, Harvard Law School, 43(B)log

The 13-factor DuPont analysis to determine likelihood of confusion is not as complex as it appears when practicing before the Trademark Trial and Appeal Board... Just two of the factors can be used to predict whether the board finds challenged marks confusing 99.57 percent of the time.

MLex, “Only 2 of 13 DuPont Factors Decide Nearly All US TTAB Cases, Research Suggests” (Jan. 9, 2026)

MarkSense Analytics. A scoring platform built from my TTAB research data. It scores trademark similarity and likelihood of confusion against decided cases. About MarkSense →

Planning a CLE, Retreat, or AI Rollout?

Tell me what your group needs. I typically reply within one to two business days.