AI products that ship to production. Agents that triage your queue, copilots embedded in your app, RAG over the docs your customers actually search. We build them in your repo, with evals you can defend in a board meeting.
Not a checklist of deliverables. Things that show up because we work the way we work.
Every build starts with a gold set and a precision/latency target. If we can't measure it, we don't ship it. You get the eval harness on day one.
No black-box "AI platform" rental. We commit to your monorepo. The code reads like the rest of your service. Your team can hire against it tomorrow.
OpenAI, Anthropic, Bedrock, Vertex, open-weight. The model is a config line, not an architectural decision. We benchmark them on your eval set.
Every feature ships with a cost/run and p95 latency number. We blow the whistle if a prompt change pushes either past your budget.
PII redaction, prompt-injection defenses, audit logs, refusal traces. Not a checkbox at the end — wired in from the first prototype.
Your engineers are in our PRs from day one. By week 4 they're reviewing ours. By week 8 they're shipping without us in the loop.
Every engagement varies. The shape stays the same.
Stakeholder interviews, prior-art audit, a written discovery doc, and a labelled gold set. End of week: a clickable prototype you can show leadership.
Eval harness in CI. First end-to-end pipeline in your repo. Cost & latency tracked. Internal demo on Friday.
Iterate on prompts, retrieval, and tools until we hit the precision / latency / cost gates we agreed on.
Staging deploy. Red-teaming. Rollout plan. Production behind a feature flag. Postmortem-style handoff doc.
A real-shaped excerpt. Names changed. Numbers honest.
engagement intake-agent = {
outcome: 'agent that triages support tickets',
success: '≥85% precision · <2s p95 · $0.04/run',
team: ['@rin (lead)', '@marco', '@anika'],
stack: ['your repo', 'your VPC', 'your eval set'],
duration: '4 weeks · fixed',
price: '$96,000',
ownership: 'you · MIT-licensed code, day 1',
} Saving us both a bad-fit call.
Yes. We also publish our own short-form MSA if you'd like a starting point.
Default yes. Most clients run inference inside their own cloud. We adapt to your model provider, key store, and observability stack.
You don't pay the final milestone. We've only had to invoke this twice in 38 sprints — both times we ended up shipping a smaller scope that did clear the bar.
A 30-minute call. A written discovery doc in a week. Fixed-price SOW by day 10.