Engagement Model
How working with us is shaped: a fixed-scope assessment, a staged build with eval gates, and a transfer that ends with your team owning the system. No per-seat licenses at any stage.
Three stages, each with its own exit
Every engagement moves through the same three stages, and each stage ends with something you keep. You can stop after any of them — the artifacts are yours either way.
1 · Assess
The AI Readiness & Roadmap assessment: fixed scope, fixed price, measured in weeks. We inventory your data and systems, rank the candidate workflows, and scope the first build. You leave with a roadmap you could hand to any builder — including your own team.
- Fixed scope and fixed price, agreed before we start
- Data and systems inventory, ranked workflow candidates
- Build plan, governance baseline, and cost model
2 · Build
The first system, built on the studio components and priced by milestone: working software at each gate, evals proving it before it moves forward. Scope grows only when a running system justifies the next piece — never as a change-order surprise.
- Milestone pricing tied to eval-gated deliveries
- Weekly working sessions with your team in the code
- Human approval gates on anything risky from day one
3 · Transfer
Ownership hand-off: code, infrastructure, prompts, eval sets, traces, and documentation move to your team, and we pair with your engineers until they run the system without us. After transfer, support is optional — a retainer for evals, model updates, and new workflows, sized to what you actually need.
- Full repository and infrastructure transfer
- Pairing sessions until your team runs it alone
- Optional retainer: evals, model routing updates, new workflows
How pricing works
Assessment is fixed-price. Builds are milestone-priced against deliverables you can run. Support is a monthly retainer you can cancel. What we do not do: per-seat licenses, usage royalties on your own system, or fees that survive the relationship. Once transferred, your only recurring costs are your infrastructure and your model usage — both of which you see directly.
A smaller way to start
The Scout product line packages the assessment motions as small fixed-price products — an AI readiness audit, an eval set built from your traces — for teams that want proof before a full engagement. Packaged products and custom builds run on the same stack, so nothing is thrown away when you graduate from one to the other.
Related learning
A fixed-scope assessment that maps your data, systems, and workflows — and returns a concrete plan for the first AI system worth building, with the governance to run it safely.
AI agents that act on business events with the tools, memory, approvals, and traces you can audit. Workflows that ship to production, not just demos.
A test set built from your production traffic that catches AI regressions before they ship. Prompt or model changes have to pass quality, latency, cost, and safety thresholds before users see them. Requires production traces to draw from.
A one-week engagement that maps your AI-readiness — what's in your data substrate, what's missing, what AI capabilities you could deploy today, and what would need to be built first.