Most AI pilots die on contact with production
An AI pilot demoed well and then died on contact with real data, edge cases, and cost.
There's obvious repetitive work that should be automated but the team can't make it reliable.
You wired up a prompt and a model and now can't make it observable, safe, or consistent.
Leadership wants an "AI strategy" but no one can separate hype from what will work.
No one owns evaluation, so no one can say whether the agent is getting better or worse.
What you get
Not hours on a timesheet — decisions made, systems shipped, and a program that works.
A working agent in production
Scoped to a real task, measured against an eval set, deployed with guardrails. Not a demo.
Evals and observability
Traces, evals, and dashboards so quality is a number, not a vibe — and regressions are caught before they ship.
Human-in-the-loop by design
Guardrails, checkpoints, and cost controls appropriate to the risk — so the agent earns autonomy over time.
Something your team can own
A runbook, handoff, and architecture your team understands — or that we operate for you on the platform retainer.
Three shapes, one operator
Start where the pain is acute. Scale as trust is established.
Agent Sprint
4–8 week fixed-scope build
$12,000 – $40,000
per month · 3-month minimum
- One agent or workflow from design to production
- Use-case assessment and agent design doc
- Eval harness with versioned test set
- Observability: traces, dashboards, cost tracking
- Guardrails, human-in-the-loop gates
- Runbook and handoff documentation
Your first 90 days
A predictable ramp with clear deliverables at each phase.
Week 1 — Assess
Rank use cases, pick the first agent, define the eval set and success bar. Deliver AI Opportunity Assessment.
Weeks 2–3 — Design & scaffold
Agent design doc; stand up eval harness and tracing; integrate the first tool or action.
Weeks 4–6 — Build to the bar
Iterate against evals until the success threshold holds. Add guardrails and human-in-the-loop gates.
Weeks 7–8 — Ship & instrument
Deploy to production behind monitoring. Deliver runbook and handoff.
Weeks 9–12 — Scale
Measure real-world performance, harden, and decide: next agent or the platform retainer.
Not the right fit?
We are selective about engagements. This may not be right if:
✗
Wants a fully autonomous system with no human-in-the-loop and no tolerance for iteration.
✗
Has no data access and no willingness to instrument systems the agent must act on.
✗
Expects a finished product after a single demo — agents earn autonomy through evaluated iteration.