Diagnose
A ranked use-case portfolio, a data-readiness verdict, and an honest list of what should not be automated yet.
Engagement model
Four phases from question to system
A deliberately short path from "should we?" to a system in production — with an explicit stop at every phase boundary.
Engagement model
Four phases from question to system
Prove
One use case against production data in a governed sandbox, measured on a metric you already report.
Harden
Security review, evaluation suite, observability, failure modes, cost controls and the runbook.
Operate
We run it while your team learns it, then hand over the platform. Success is you not needing us.
Why us
Five reasons clients choose a specialist
Production-first, not AI demos
We are measured on systems running in your estate under load, with owners, SLAs and an on-call rota — not on a proof of concept that impresses a steering committee and then quietly expires.
Vendor-agnostic architecture
OpenAI, Anthropic, open-source weights, Azure, Databricks, NVIDIA or your own metal — chosen on fit, cost and risk, and swappable when any one of those changes.
Founder-led execution
The senior engineer who scopes your architecture is the one who writes it. No pyramid, no handover to a bench.
Built for regulated ground
Governance, traceability and data residency are the first design constraint, not a retrofit before go-live.
Reusable accelerators
Document intelligence, agent orchestration and evaluation scaffolding arrive pre-built, so your budget buys domain fit rather than plumbing.
Knowledge transfer by default
Every engagement ends with your team operating the platform, the runbook written and the accelerators in your repository.