LLM application development
Products built on language models, with evaluation from day one.
The problem
What usually brings people here.
The demo was convincing and the pilot is not. It is right most of the time, nobody can say how often, and being wrong in front of a customer costs more than being slow. That gap between demo and product is evaluation, and it is most of the work.
What we do
How the work actually runs.
Evaluation from day one: a graded set drawn from your real cases before we tune anything, so a change can be shown to have helped. Then the unglamorous parts — retrieval, prompts under version control, fallbacks, cost and latency budgets, and a human path for the cases the model should not own. You get the eval harness as a deliverable, not just the app.
How this runs
Design, develop, refine.
Design
Two to four weeks. We scope with the engineers who will build it, so the estimate comes from the people held to it.
Develop
Two-week increments, demoed to you, shipped behind flags. You see working software in week three, not a status deck.
Refine
The squad stays. Lead time comes down, the backlog gets shorter, and the same people know why every decision was made.
Proof lives on the work page.
We publish numbers per engagement, cleared by that client, rather than per service line. What is written up there is what we are allowed to show.
Also in AI Engineering
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You will get a reply from an engineer, not a form handler. If we are not the right firm for it, we will say so and tell you who is.