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 short path from "should we?" to a system in production. Every phase ends with a real stop, so you can change your mind before the next one starts.
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
Six reasons clients choose a specialist
Production-first, not AI demos
Judge us on software running in your estate, under load, with an owner and an on-call rota. Not on a demo that wins a steering committee and quietly dies.
Vendor-agnostic architecture
OpenAI, Anthropic, open-source weights, Azure, Databricks, NVIDIA or your own metal We pick on fit, cost and risk, and we keep every one of them swappable.
Founder-led execution
The engineer who scopes your architecture is the one who writes it. Nobody hands you off to a bench after the pitch.
Built for regulated ground
We design for governance, traceability and data residency on day one. Bolting them on the week before go-live never works.
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.
