Leader · Builder · Applied AI

I build systems that must be right.

Fifteen years turning enterprise data and AI from strategy into shipped, governed systems - across financial services, insurance, and life sciences. I also write about the part nobody warns you about: where agentic AI quietly breaks in production, and how to engineer around it.

Led

  • 75+ engineers led across enterprise teams
  • $317MM+ realized and projected value - cost reduction, automation & ML $52MM realized cost avoidance + $265MM projected 3‑year profit from ML
  • 1.1M documents a year processed at 80% lower cost

Built

  • model-eol

    A machine-readable model deprecation format and zero-dependency CI checker.

    npx model-eol . --days 90

    Open source · npm · MIT

  • Adaptive Academy

    A local-first AI tutor that won’t give you the answer until you’ve tried. The code enforces it.

    Open source · Docker · Apache 2.0

Line counts 14/7/4 and 2 gated are illustrative weights, not measurements.

Drawn by code, not generated by a model: every figure on this site is a deterministic render - the same discipline the essays argue for, applied to the essays themselves.

Tom Sullivan

About

I’m Tom. I’ve spent fifteen years building data and AI systems in industries where a wrong answer costs real money - pharma, consumer finance, insurance, and now private equity. The question that runs through all of it: not “can AI do this?” but “can you trust what comes out enough to act on it?” This site is where I work that question in public. The writing and views here are my own.

  1. Now

    Advisory Lead, Applied AI - West Monroe

    Lead architect and technical leader for a new 50-person Applied AI practice delivering AI strategy and forward-deployed engineering for private equity firms and their portfolio companies. Built an outside-in research-synthesis platform for PE diligence, with the MVP released in 8 weeks.

  2. 2024 - 2026

    Data & AI platform lead - Group 1001 (insurance)

    Led the platform teams behind the group’s document AI and data estate - ~960k orchestrated production jobs a year at a 99.4% success rate, 1.1M documents a year processed at 80% lower cost. The transfer-automation work won the 2025 Gartner Eye on Innovation Award.

  3. 2021 - 2024

    ML platform lead - Discover Financial Services

    Led the build of a high-performance ML platform - three teams, ~40 engineers - that accelerated model deployment by 60% and supported 50+ models projected to drive $250MM+ in three-year profit before tax.

  4. 2018 - 2021

    Automation organization lead - Discover Financial Services

    $52MM in annual cost avoidance across an enterprise automation portfolio.

  5. Foundations

    Georgia Tech & Loyola Chicago

    MS in Computational Analytics; BS in Biophysics (cum laude).

The fastest way to reach me: [email protected] or LinkedIn.