For companies that already have a product and a team, this is a short engagement that rebuilds the parts AI now does better, puts evaluation and telemetry underneath them, and leaves your own developers able to carry it. No embedded squad, no staff augmentation, no permanent seat on your payroll.
You have a product that works and a roadmap that has stopped moving, because the interesting work now needs skills the team has not had time to build. Hiring for it takes a quarter you do not have, and staff augmentation gives you people who leave with everything they learned. A short push with handover fixes the gap without creating a dependency.
Where the product spends its users' time, where your team spends theirs, and which of the two AI actually changes. Usually there are one or two places where it does, and a dozen where it would just add cost and a new failure mode. Saying which is which is the first deliverable, and it is short.
Everything is built in your repository, in your patterns, with your developers reviewing as we go. The point is not to hand you a black box that works; it is that after we leave, the person who has to change it in six months can read it, run the evaluations, and understand why it is shaped the way it is.
AI features fail quietly — a prompt drifts, a model changes, quality slides and nobody sees it until support does. So we install the boring half: evaluation sets, telemetry on the paths that matter, and a dashboard that shows cost per request next to quality. It is the difference between shipping a feature and being able to keep it.
Thirty minutes with whoever knows the product best. You leave with our honest read on where AI helps and where it would just add cost.