How the work actually runs.

One call with the people who know the problem, then a written brief back to you within two working days: what we understood, what we think the hard part is, what is explicitly out of scope, and which of the four engagements fits. If none of them fits we say that instead of reshaping your problem to match a price list.

Before any prompt is written we build a labelled set from your real examples with your domain experts, split by category, with a held back portion. The pass threshold goes in writing, with the consequence of missing it agreed at the same time. This is the week that makes every later argument about quality a number rather than an opinion.

One path through the system, end to end, running in your cloud account, usually inside the second week. Not a prototype on a laptop. Deploying early is how integration risk, credential problems and data access surprises surface while there is still time to change the plan.

Every week ends with a working demonstration against the evaluation set rather than a status document. You see the score, the failures, and what we are doing about them. Anything at risk is raised in the week it becomes at risk, not in the week it becomes a problem.

Guardrails on the output path, escalation payloads, tracing, cost and latency instrumentation, alerts wired to people who can act, and runbooks for the two or three ways this specific system fails. Where the system can act, it shadow runs against live traffic before it is granted authority.

Your engineers make the last change while we are still there to watch. Repository, infrastructure as code, evaluation suite, documentation and access all sit with you, and none of it depends on an account we control. If you want us to stay, that is an Embedded AI Pod with its own scope, not a dependency we engineered into the build.