Production AI systems, engineered to last.
LLM applications, intelligent agents and automation that survive contact with real users, real data and real compliance requirements.
Why this is hard.
Most AI initiatives die between the demo and production. A prototype that impressed the board quietly fails on edge cases, costs spiral with usage, and nobody owns evaluation, monitoring or the failure modes. The gap isn't the model — it's the engineering around the model.
Hiring for this in-house is slow and expensive: AI engineers are scarce, and the field changes monthly. You need people who have shipped production AI systems — not experimented with notebooks.
What we do.
- LLM applications — retrieval, structured output, tool use and multi-step workflows built on the right model for the job
- AI agents and multi-agent systems that act on your data and systems, with guardrails and human approval where it matters
- Intelligent automation — replacing manual, repetitive workflows with reliable AI-assisted processes
- Evaluation and testing pipelines, so quality is measured, not assumed
- Cost and latency engineering — caching, routing and right-sizing models so unit economics work at scale
- Integration with your existing systems, data and access controls — not a bolt-on chatbot
What you get.
A first working system
A first deliverable evaluated against your data. Scope, access and acceptance criteria determine the schedule.
Quality you can defend
Every system ships with evaluation baked in, so you can show stakeholders what works and what improved.
Your system, documented
Architecture, decisions and runbooks documented under our methodology — no consultancy lock-in.
What are you working on?
Fragmented data, a process to automate or a system to build — tell me what needs to change.
Let’s talk
Book a free 30-minute chat with me. We’ll see whether I can help.