We start every AI conversation with two questions: what does a wrong answer cost, and what does a right answer save? If the first number is high and the second is small, we will recommend not shipping a model at all — a rules engine, a better search index or a well-designed form is often cheaper, faster and more honest.
When a model is the right answer, we treat it like any other unreliable dependency. There is an evaluation set before rollout, a cost ceiling per request, caching for repeated work, a timeout, and a defined behaviour for the moment the provider has an outage. Output that affects money or health goes through a human review path.
We also write down what the feature costs per active user per month, because AI features have a habit of quietly becoming the largest line on the infrastructure bill.
What you get
Evaluation set built before any rollout
Per-request cost ceilings and caching
Graceful degradation when the model fails
Human review path for high-stakes output
Monthly quality and spend report
Typical stack
Claude APIVector searchPostgreSQLQueue workersEvaluation harness
Not sure this is the right service?
Describe the outcome you want instead of the deliverable you think you need. We will tell you which service fits — or tell you honestly that you do not need us yet.
Kotlin and Jetpack Compose, built for the device spread that actually shows up in your analytics.
Kotlin and Compose interface
Material 3
Play Billing and offer management
Data safety form and policy compliance
5–10 weeksfrom $18,900
Let’s scope it properly
Tell us what you want to ship. We will tell you what it really takes.
Send us the shape of your idea and we will come back with a written scope, a realistic timeline, a fixed price band and the risks we would want to kill first. No decks, no discovery invoice, no pressure.