Agents that do a job.
A single task, done reliably, without a person in the loop. Document extraction, qualification, triage. Scoped narrowly on purpose — a narrow agent that works beats a broad one that mostly does.
Services · AI Engineering
AI that survives its first real user.
Most AI projects work in the demo and break in production. We build for the second one — with the evaluation, observability, and cost controls a prototype never needed and a product can't launch without.
Three kinds of work
Workflows with humans in them.
AI and people working the same process, with defined handoffs and a person on the decisions that need one. Most valuable AI work looks like this, not like a chatbot.
AI inside the product.
Capability built into software your customers already use, rather than a separate tool nobody opens twice.
How we work
Evaluation before optimisation.
We instrument first. If you can't measure whether an answer got better, you're guessing — and guessing gets expensive at scale.
Cost is a design constraint, not a surprise.
Token metering, caching, and model routing are decided at architecture, not discovered on the first invoice.
Your data stays yours.
We build inside your infrastructure and your accounts. Nothing leaves your environment unless you decide it should.
Five questions
Whichever fits the problem. Anthropic and OpenAI most often, open models where cost or data residency demands it. We're not on anyone's partner programme and we don't take referral commissions.