Four systems I've written up in depth, and a longer list of projects and engagements. Filter by the kind of work you're interested in.
Legal practices — plaintiff, defense & injury
Helps attorneys make sense of thousands of pages of medical records — without patient details ever reaching an outside AI service, and with the same answer every time the case is run.
Read case studyHealth plans & payers
Turns piles of messy claim documents into clean, structured summaries, so physicians spend their time deciding instead of reading.
Read case studyU.S. government transit authority
A private, ChatGPT-style assistant that lets thousands of employees ask questions about internal documents — with every conversation logged and nothing leaving the organisation.
Read case studySoftware products — with a module for AI applications
A tool that uses AI to look for security holes the way a human tester would — thinking about each specific app — and proves every problem is real before reporting it.
Read case studyData-sensitive enterprise
Adapted an open-weights model to the client's domain, compressed it to fit their existing GPUs and served it inside their own network, so no request ever left. The project existed because a hosted API wasn't an option.
Customer support
Speech in, reasoning and tool calls in the middle, ElevenLabs speech out. Most of the engineering is about timing — a reply that arrives a beat late stops feeling like a conversation — so the pipeline is built around latency.
Product engineering teams
A domain eval set with automated scoring, wired into the delivery pipeline, so a prompt change, model swap or new quantization can't ship if it makes the task worse. It turned “it feels better” into a number the team could discuss.
Operations teams
A multi-agent system that plans a task, calls the tools it needs and pauses at set checkpoints for a person to decide. The escalation points are explicit, so the agent knows what it isn't allowed to finish on its own.
Product engineering teams
An authorised penetration test run through the harness — the model handling recon and targeted test generation, with every finding reproduced before it reached the client. Delivered ranked, with fixes attached and a re-test to confirm them.
Operations & internal tooling
AI steps added to the workflows a business already runs on. n8n handles triggers, integrations and retries; the model does only the part that needs a model. Much of the value was deciding which steps should never be an LLM call.
SaaS product company
Built the company's product site and embedded an AI assistant into the core product, so users get answers in context without leaving the interface.
Technology consultancy
Led a team of six through adopting modern AI workflows and tooling while delivering three full-stack AI projects to production.
Independent clients
Ongoing freelance work: retrieval systems, domain chatbots and end-to-end AI implementations, scoped and delivered directly with each client.
By capability
Each page explains the area in plain terms, then links the projects and blueprints that go deeper.
Contact
I'm open to AI engineering, architecture and training work. Tell me what you're building and what the constraints are — that's usually enough to start.