Technical founder building AI-powered systems for healthcare

I'm CTO and co-founder at Pickle, where we're building the data infrastructure for healthcare recruiting. We process millions of healthcare professional records using LLM-powered entity resolution and enrichment, helping recruiters find and verify candidates faster.

Before Pickle, I architected data platforms and AI systems powering £9M products and led enterprise digital transformations for global financial institutions and FTSE 100 companies. Now I'm focused on what happens when you combine messy real-world data with modern AI to deliver simple systems that deliver measurable results.

🥒 Pickle — Healthcare recruiting platform with LLM-powered entity resolution and enrichment across licensing, credentialing, and professional data.

💒 OSWP - opinionated copy of The Knot in NextJS as my partner and I prepare for our wedding.

🦾 Scrape GPT - Intelligent web scraping system that combines deterministic XPath extraction with LLM-powered adaptation.

🏥 npi-mcp — MCP server for NPI database access (coming soon)

• Build with LLMs — Entity resolution, intelligent scraping, agent workflows in production
• Work with customers — Technical founder who's done sales, onboarding, and support
• Ship in regulated domains — Healthcare credentialing, licensing data, compliance constraints
• Lead small teams fast — Startup-speed execution with enterprise-grade thinking

• LLMs in production — Entity resolution, data enrichment, and intelligent recruitment at Pickle
• MCP (Model Context Protocol) — Building tools that connect AI systems to real-world data
• Healthcare data architecture — Person-centric data models over fragmented licensing systems
• Open Data Contract Standard — Technical Steering Committee member

Python | FastAPI | PostgreSQL | Claude API | MCP | LLM Orchestration
TypeScript | Next.js | Graph Databases | Azure | AWS | Terraform | Data Architecture | Data Governance

I'm always interested in connecting with fellow technical leaders and discussing how we can build better systems together.

"Building systems in the messy middle between AI capabilities and real-world constraints is like city planning: transportation, utilities, and zoning all have to be intentionally designed for the city—and the business—to actually work."