Selected work · client engagements anonymized
01 PRODUCTION · LEGAL AI
A private AI research system that never leaves the building
- Problem
- A solo law practice needed AI leverage on privileged case material — but privileged data can't touch the cloud, which put every mainstream AI tool off-limits for exactly the highest-value work. In legal, a fabricated citation isn't a UX annoyance; it's a malpractice risk.
- Approach
- I built a fully air-gapped system that runs on the firm's own hardware: a local open-weight LLM paired with hybrid retrieval — vector search plus a knowledge graph — so every answer is grounded in the actual case record. I selected the model through a formal bake-off scored on citation faithfulness (94.9%) and keyword recall (92.6%), not on vibes.
- Outcome
- Live on-prem, with an evidence-sweep capability and an operating guide the attorney uses directly in casework. No data ever leaves the office.
Signal: data sovereignty as product strategy · evaluation discipline · full-stack local deployment
02 PRODUCTION · WORKFLOW
Turning slow, leaky intake into instant qualified routing
- Problem
- A multi-state firm was losing leads to slow manual intake. Speed-to-response is the single biggest lever on lead conversion, and theirs was measured in hours.
- Approach
- I built an automated intake product that qualifies inquiries, routes each one to the right partner by jurisdiction, and fires instant notifications — white-labeled to the firm's own brand.
- Outcome
- A repeatable lead-generation engine rather than a one-off build — designed to be reused across future clients.
Signal: business-outcome framing · productization · speed-to-lead as the metric that matters
03 0 → 1 · SAAS
A job-application autopilot, built end to end
- Problem
- Applying for roles is high-friction and repetitive — easy to do, hard to do well at scale.
- Approach
- I designed and built the full product solo: a web app plus a browser extension that autofills applications with fuzzy field detection, backed by an LLM. Including the hard parts — the extension, and mapping messy real-world forms.
- Outcome
- Near-launch, owned end to end — product, backend, and the browser layer most people avoid.
Signal: zero-to-one ownership · full-stack execution · the unglamorous last mile
Also in flight
PaySwitch AI — a provider-neutral advisor for switching payment processors, drawn from payments domain depth built at Mastercard. A market gap I spotted, scoped to a phased MVP.
Capabilities
Product
$20M+ incremental revenue · Mastercard
0 → 1 product ownership
evaluation & benchmark design
exec-level tech assessment
GTM strategy
Account Level Management
AI & Systems
local + cloud LLM deployment
RAG + hybrid retrieval
vector databases
knowledge graphs
embedding-model selection
model evaluation
Chrome extensions
Next.js / FastAPI / Postgres
Domain
payments & fintech
legal tech
SMB operations
Credentials
Generative AI with LLMs · DeepLearning.AI
AI Product Management · Duke
Claude Code in Action · Anthropic
AI Fluency · Anthropic
AWS ML Engineer Associate · in progress