An enterprise AI development company that clears security review
We build enterprise AI with the parts that decide whether it ever goes live: scoped credentials, per-step audit trails, documented blast radius, and a human oversight design. Getting that right at the start is a week. Retrofitting it is a quarter.
No sales script. You talk to the engineers who'd build it.
Our team works a shifted day so you get real-time standups and same-day turnarounds in your time zone, not next-morning replies.
Every line of code, model weight, and prompt is yours from day one. NDAs and clean IP assignment are standard, not an upsell.
You work directly with the engineers building your system. No account managers sitting between you and the people writing code.
We move from scoping to a working system in production in weeks. Most engagements ship something usable inside the first month.
What we build
Concrete systems we ship, tuned to your data and your stack.
Security review readiness
Scoped credential per agent, explicit write allowlists, blast radius documented, and a complete log. The questions your reviewer will ask, answered before they ask.
Audit trails and oversight
Per-step records of inputs, tool calls, and carried state, plus a stop button that leaves downstream systems consistent.
Data residency and self-hosting
Open weight models inside your own VPC or on-premise when policy means nothing leaves your infrastructure.
Integration with what you already run
ERP, CRM, mainframes, and vendor portals with no usable API. This is where enterprise projects actually stall.
How we work
Scope & evals
We pin down what success means and build the evaluation set before writing the feature, so quality is measured, not guessed.
Build in the open
Weekly demos against real data. You see progress every week and can change direction before it gets expensive.
Ship & instrument
We deploy with logging, cost tracking, and guardrails in place, then tune against production traffic.
Hand off or stay
Take the keys with full docs, or keep us on for iteration. Either way you're never locked in.
Questions, answered
Can you work inside our cloud and security constraints?
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Yes. Your cloud account, your GitHub org, behind your VPC, with your identity provider. We are used to working where the network is locked down and the approvals are real.
What about the EU AI Act and similar regulation?
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The high-risk obligations moved to December 2027, but the transparency and AI literacy duties apply now. More usefully, the logging and oversight those rules demand is the same work that makes an agent debuggable, so we build it regardless.
Our procurement process is slow. Does that break your approach?
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It is the most common critical path, which is why we start credential and access provisioning in week one before any code is written. Planning around it works. Ignoring it is how teams end up borrowing an over-permissioned service account.
Do you work alongside our internal engineering team?
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Often, and it is usually the better arrangement. We join your repo, match your conventions, ship as PRs your engineers review, and leave the team able to maintain it.
Let's scope your build.
Tell us what you're trying to ship. We'll tell you honestly whether AI is the right tool and what it would take.