For enterprise Deploys in your VPC DPA and security review supported EU-based team

Enterprise AI that actually ships.

Most enterprise AI never leaves the pilot. Not because the model was wrong, but because nobody owned integration, security review, evaluation or the change in how people work. That gap is the job.

WHERE ENTERPRISE AI STALLS

The pilot has no route to production

A demo built against a CSV export cannot reach the system of record. Nobody scoped the integration, the permissions model or the failure path — so the pilot succeeds and then stops.

Security review arrives too late

The architecture is chosen, then infosec asks where data flows, which sub-processors are involved and how prompt injection is handled. The answers require a rebuild.

Nobody can say whether it works

Without an evaluation set agreed up front, "is it good enough" becomes a matter of opinion, and the loudest sceptic in the steering committee decides.

HOW WE APPROACH IT

Design for the security review
on day one.

The constraints that kill enterprise AI projects are known in advance: where data may live, which models are approved, what has to be logged, who signs off on an automated decision. Treating them as an afterthought almost always means rework; treating them as the initial design input is close to free.

So we start from the deployment target and work backwards. If inference has to run in your VPC, that decides the model options before any prompt is written. If decisions get audited, the trace format is designed before the agent is. If your data cannot leave the EU, that is settled in week one rather than discovered in month four.

The result is usually a less exotic system than a greenfield demo — and one that reaches production, which is the only comparison that matters.

Phase 01

Discovery

Systems, data, constraints and the decision the AI is meant to support. Ends with a written architecture and an evaluation plan you can circulate internally.

Phase 02

Pilot

A narrow slice built against real systems and real data — not a sandbox. Measured against the evaluation set agreed in discovery.

Phase 03

Production

Monitoring, regression gates, runbooks and handover. Either your team owns it or we support it under a defined arrangement — decided explicitly, not by default.

WHAT WE BUILD FOR ENTERPRISE

QUESTIONS

QUESTIONS — 5

Yes. We deploy into a client VPC on AWS, Azure or GCP, and we can run entirely on open-weight models on your own hardware where no data may leave the perimeter at all. The trade-off is real — self-hosted open models are behind frontier APIs on the hardest reasoning tasks — so we scope which parts of a system genuinely require that constraint rather than applying it uniformly.

An architecture document covering data flows, storage and retention; the sub-processor list for any third-party model provider involved; our approach to prompt injection, tool permissioning and secrets handling; and completed responses to your security questionnaire. We can sign a DPA. Where a control is not yet in place we say so explicitly rather than answering aspirationally.

Any external model provider is a sub-processor and gets named as one. We configure zero-retention endpoints where the provider offers them, keep the provider list explicit in the architecture document, and design so a provider can be swapped without rewriting the system — which matters both for procurement and for the day a model gets deprecated.

You do. Code is delivered into your repositories, infrastructure is defined as code in your accounts, and any fine-tuned weights are yours. We do not retain a runtime dependency on us; if you want your team to take over at the end of an engagement, that is a supported outcome we plan for rather than a threat.

Discovery is typically two to four weeks. A pilot against real systems is usually six to ten weeks depending on how many integrations are in scope and how long access provisioning takes — which is genuinely often the critical path. Production hardening adds four to eight weeks. Anyone quoting you a firm figure before seeing your systems is guessing.

FOR ENTERPRISE — ALL PAGES