Three phases from a clean AWS account to agents doing real work under supervision.
You give us a capped, federated role. We deploy the stack inside your boundary, expose your systems as a capability contract you can read in an afternoon, and go live behind an approval queue — then keep the whole thing honest with self-review on every turn and golden conversations on every release.
Three phases. No rip-and-replace, no consultants in your conference room.
Your account, our stack.
You provide an AWS account and a capped, OIDC-federated role — no long-lived keys, no standing human access. We deploy the full agent stack inside your boundary: durable workflow engine, vector memory, realtime transport. Your data and your credentials never leave.
Your systems, exposed as tools.
We map the job that's actually being done, then expose the systems behind it as curated, task-level tools — each classified by blast radius, each mutation gated. Not database access. Not screen-scraping. A capability contract you can read in an afternoon.
Under review, then under supervision.
Agents go live behind an approval queue. Every action logged, replayable and reversible; every run bounded by token, cost and wall-clock ceilings with a kill switch. You widen autonomy as the evidence earns it — not because a slide told you to.
Pre-built where your stack is common. Bespoke where it isn't.
Connectors are built on the Model Context Protocol, so a capability written once is reusable across deployments. Common enterprise systems get a maintained connector; the software that only your business runs gets a bespoke one, built with your team and versioned like the rest of the fleet.
Each connector exposes task-level tools rather than raw tables — typed, classified by blast radius, every mutation gated. That contract is the thing your security team reviews, and it is short enough to read in an afternoon.
Talk to us about your stack →A deployment is a living thing. Two gates keep it honest — one per turn, one per release.
It checks its own work, twice.
Mid-task the agent reviews whether it has drifted from what you actually asked, so it corrects course before going further down the wrong path. Then, before an answer reaches you, a separate reviewer model checks it against the full request — the part of a multi-part ask that quietly got dropped is caught there.
Golden conversations run as a merge gate.
A change that breaks how an agent handles a real scenario doesn't ship. The eval framework was built before the tools were, deliberately — eval gaps are the single most common failure pattern in agent deployments, where systems that pass curated tests fall over the moment real input arrives.
What we need to start is smaller than you think.
A clean AWS account and a capped, federated role. One operational workflow that genuinely hurts. And access to the people who actually do that work — that last one matters most.