Regulated AI / Healthcare · Life sciences · Financial services
Fifteen years shipping production AI in regulated, data-sensitive industries — healthcare, life sciences, and financial services. I take agents and ML systems from prototype to audit-ready, with the evals, guardrails, and SOC2/HIPAA evidence that let Legal, Security, and Compliance all say yes.
01What I do
Regulated industries don't need more demos. They need AI that ships — agents and pipelines that are measured, bounded, and audit-ready, built end to end from architecture through production.
Agentic systems with tool-routing, hybrid retrieval (RAG), and guarded text-to-SQL — deployed where work already happens: Microsoft Teams, Copilot Studio, and zero-trust corporate networks, with managed-identity auth throughout.
AgentsAI output gets measured and bounded, not trusted blindly. Deterministic eval harnesses, type-safe agent loops, and objective gates that run before any human approval — a thick boundary around a creative interior.
EvalsFragmented operational data unified into a single source of truth — LLM classification against domain rules, probability-weighted forecasting, idempotent re-runs, and strict separation of sensitive identifiers from shared reporting.
PipelinesSOC 2 Type II run end to end — gap analysis, control-policy authoring, evidence, audit readiness — plus HIPAA-aware architecture, PHI-safe data lanes, and security boundaries reviewed with zero high/critical findings.
SOC2 / HIPAAA clear-eyed read on where your organization actually is — the controls in place, the gaps that block deployment, and a sequenced path to a governed pilot.
Assessment02Selected work
Recent engagements building AI agents, evaluation systems, and data pipelines for regulated, data-sensitive organizations.
Client and proprietary product names omitted · technologies and architecture described in full · most delivered solo or in small teams, end to end.
Federal research program
A natural-language agent for clinical-trial site feasibility over hundreds of thousands of documents — tool-routing across hybrid (vector + keyword) search, a guarded read-only text-to-SQL pipeline, and peer-adjusted feasibility scoring. OCR fallback lifts effective corpus coverage to ~99.9%; a JWT/JWKS-hardened bot ingress passed security review with zero high/critical findings.
Global information-services firm
Two production agents deployed inside a zero-trust corporate network — a project-discovery agent mining tens of thousands of engineering work items, and a product-knowledge agent over hundreds of mixed-format documents — surfaced through a Copilot Studio chatbot, with managed-identity auth throughout and a search-quality evaluation harness.
Healthcare AI company
A multi-service platform letting clinicians query real-world data and literature with LLM synthesis — React/TypeScript front ends, a SMART-on-FHIR OAuth flow into EHR systems, a graph-based Python search service, and an MCP tool-server exposing platform capabilities to third-party LLM clients with PHI-safe handling.
Biotech
An end-to-end conversational screening prototype over public trial registries and biomedical literature — tiered cross-source matching, semantic retrieval with a three-state eligibility model (match / no match / not specified), composite-score ranking, and a conversational UI with a live audit diagram and full provenance.
Runs an AI coding agent in isolated git worktrees and gates output against objective checks — correctness, latency budgets, extraction F1, schema and migration safety — before any human approval.
Static typing and boundary validation that catch AI-generated errors at the edge, with a strict split between the production runtime and the offline eval.
A gated build-vs-adopt evaluation of a vendor SDK against a battery of auth and channel tests that shaped a downstream production decision.
A weekly pipeline unifying fragmented operational systems into one source of truth — LLM classification against domain rules, probability-weighted expected value, and prioritized, owner-assigned action queues.
Cash-flow reconciliation across accounts with trend-based runway forecasting, plus a set of operational automation and cost-ledger tools with strict data-separation rules.
Ran a SOC 2 Type II engagement end to end — gap analysis against the trust-services criteria, authoring and rationalizing the control-policy set, organizing audit evidence, and driving audit readiness with a quantified risk-budget model and adversarial review cycles.
03How I work
Least-privilege access and explicit trust boundaries are designed in, not bolted on.
Deterministic gates and honest measurement — output is judged, never trusted blindly.
Protected identifiers stay isolated from anything shared or reported on.
Tests, infrastructure-as-code, and documentation come with the delivery.
04Writing & thinking
Latest essay
Career advice usually arrives as a smoothed biography. Step through the mirror instead, look hard at three terrible ideas, and see what they reflect back.
Read essay →Essay · 9 min
A physicist's framework for changing your life — feel the local slope, take one small step downhill, and repeat. Why the modest algorithm beats the wholesale transformation, and the rare moment it doesn't.
Essay · 8 min
The unglamorous habits — real evals, tests, contracts at the seams — that keep AI-assisted building from collapsing into throwaway spaghetti. Eight rules I actually use.
Essay · 5 min
DeepSeek at $0.14 a million tokens and $160 for an hour of a frontier model are two points on the same curve — not an argument about whether AI is cheap.
Essay · 6 min
The longest task an agent completes reliably — and why the curve is steeper than your roadmap assumes.
05Experience
Dodecaplex LLC
Governed Teams agents on Azure; evals, guardrails, and SOC2 evidence packs; Fabric/FHIR pipelines.
Fortrea · Global CRO
Established MLOps and AI governance across a 19,000-person clinical research organization.
Lucence · Genomics diagnostics
Built the US lab from the ground up and scaled US IT.
Global medical-technology company
Real-time inference from 200+ cancer centers; CI/CD and model deployment in an FDA-regulated environment.
CliniCast · acquired 2015
Cloud platform and discharge-forecasting models from inception — 85% accuracy in clinical use.
06Get in touch
The best first step is a short scoping call. Bring a workflow you'd like to make governed and audit-ready, and we'll talk through what's involved.
Book a 20-min call →