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Model selection based on measured task performance rather than benchmarks. Fine-tunes where they earn their cost, and routing that keeps quality up while spend comes down.
Scoped to reach production, with the evaluation criteria agreed before a line of code is written.
Fine-tuning, evaluation harnesses and model routing.
Model selection based on measured task performance rather than benchmarks. Fine-tunes where they earn their cost, and routing that keeps quality up while spend comes down.
Task-specific evaluation suites
Fine-tuning & distillation
Cost-aware model routing
The same sequence on every engagement, whether it runs nine weeks or nine months. Nothing carries over on trust alone.
01Discover
A paid two-week audit of your processes, data and systems. We come back with a ranked list of what AI should touch — and what it should not.
Audit report and ranked backlog2 weeks
02Architect
Model selection, retrieval design, guardrails and the integration surface. You get a written architecture with a cost model attached to it.
Architecture doc with cost model1–2 weeks
03Build
Two-week sprints with a working agent at the end of each one. Your team reviews real output, not slideware, from the third week onward.
A working agent every sprint4–8 weeks
04Evaluate
A task-specific eval suite gates every release. Nothing reaches production until it beats the baseline on your data, not a public benchmark.
Eval suite and release gateContinuous
05Operate
Tracing, drift alerts, cost dashboards and an on-call team who already know your stack. We stay after go-live — that is the whole point.
Live dashboards and on-call rotaOngoing
Bring one process you think an agent could run. We'll tell you straight whether it's worth building — and what it would cost if it is.