Two AI pilots. Production-shaped. Four to eight weeks.
Most AI pilots never reach production. We design these two to be production from day one: identity, observability, guardrails, cost attribution. Real users on at least one of them by week eight.
Agentic Kickstarter
No diagnosis, no charge.
If after week one of the Agentic Kickstarter you don't have a written architecture decision pack — use cases agreed, guardrails named, success metrics defined — you can stop the engagement and pay nothing. We've never invoked this clause; we're prepared to.
What's included.
- [01]
Use-case discovery workshop
Three to five candidate use cases. Two picked together. Success metrics agreed in writing.
- [02]
Secure pilot environment
Identity, data egress, model access, observability. Built on your landing zone, not a side cluster.
- [03]
Two pilots, integrated with CI/CD
Production-shaped. Real users on at least one. Token, latency and quality dashboards from t=0.
- [04]
Guardrails and observability
Input validation, output review, hallucination class identified, fallback paths. Written, not assumed.
- [05]
Adoption roadmap
Decision tree for what scales, what stops, what waits. Quarterly review optional.
- [06]
EU AI Act readiness
Risk class identified, transparency obligations met, evaluation evidence shipped with the pilot.
How the Agentic Kickstarter runs.
One-week discovery.
Three to five candidate use cases. Two picked together. Success metrics in writing.
⏱ 1 wkPilot architecture.
Identity, data, observability, guardrails. Signed off by your security lead.
⏱ 1 wkTwo pilots, 2–6 weeks.
Production-shaped. Real users on at least one. Dashboards from day one.
⏱ 2–6 wksAdoption review.
What worked, what didn't, what to scale, what to retire. Your team runs it from here.
⏱ 1 wk[03] / Underpinning services
→ WHAT SITS UNDERNEATHQuestions about the Agentic Kickstarter.
[01] What if one pilot fails? +
Half of pilots should fail. That's the point of running two. The adoption review names what was learned, what to retire and what to scale. A failed pilot is still a useful artefact.
[02] Do we need a landing zone first? +
Not strictly. We can build the pilot environment as a stand-alone account or subscription. We will tell you honestly when a landing zone is a precondition (data residency, regulated workloads).
[03] Which models do you support? +
Bedrock, Vertex AI, Azure OpenAI, OpenAI direct, and open-weights on managed runtimes. We pick on data residency, latency, total cost, exit risk.
[04] What about hallucinations? +
Identified as a class per pilot. Mitigations and fallback paths written into the runbook. Quality regression dashboards live before the pilot meets a real user.
Ready to start the Agentic Kickstarter?
Fixed scope, fixed timing, fixed price where applicable.