AI systems I've built

A pipeline that analyses any company's trademark portfolio and surfaces unprotected marks, expired marks, renewal deadlines and geographic gaps, turning raw data into a ready-to-send sales brief in about seven minutes per company.

On one construction group: 1,110 trademarks across 66 jurisdictions analysed, 9 unprotected marks detected. Built to run across 1,000+ companies a year.

One assistant that switches between teaching (trademark questions across 91 jurisdictions, answers constrained to a sourced knowledge base, no hallucination) and selling (qualifying prospects with tact coded in).

One case per session, honest portfolio segmentation, even telling small portfolios they may not need the product.

A system that regenerates the legal knowledge base for 91 jurisdictions every quarter, unattended, in roughly 18 to 24 hours, then notifies itself when done.

Around $314 per quarter to keep a 91-jurisdiction base current. A small team moving like a large one, made literal.

A retrieval system over the EU AI Act and GDPR that returns exact source text with full provenance, no AI paraphrase, built for people who must cite the real wording.

Hybrid search (semantic + lexical, fused with RRF) reaching recall@5 of 1.000 on the AI Act. I caught an infrastructure bug where the index had been running at ~4% recall and fixed it to 100%. 18+ documented architecture decisions, honest evaluation findings including the failures.