What we do
Four practices, one standard.
The standard: it holds up in production. Everything below is described by its mechanism — what we actually do, what you actually receive — because adjectives are not checkable and mechanisms are.
Agent systems
Agents that earn their autonomy
We build AI agents under graduated autonomy: approval gates on everything at first, autonomy expanded only where the evaluation record earns it.
Models make mistakes. We assume it, measure it, and build the system that catches it before your customer does. Every agent ships with an evaluation harness that runs against production traffic, human-in-the-loop checkpoints where the stakes require them, and an audit trail of every action taken. Autonomy is a dial we turn with evidence, not a switch we flip on day one.
For workflows where a working agent changes the economics of a business function.
What you receive
- The agent, in production, doing measured work
- An evaluation harness you keep and extend
- Approval-gate configuration and the record that justified each relaxation
- Runbooks for the failure modes we planned for
Private inference
Models inside your perimeter
On-prem and in-VPC deployment of open-weight and frontier models. Your data stays inside your perimeter; there is no traffic we can see.
For regulated buyers, “the data never leaves” is a gate, not a preference. We deploy and operate inference inside your cloud tenancy or on your hardware, wire it to your identity and audit systems, and hand over the keys. The weights are yours, the logs are yours, and our access ends when the engagement does.
For organizations where data residency and provider independence are contractual requirements.
What you receive
- Inference serving inside your VPC or on your metal
- Model selection benchmarked on your workload, not on leaderboards
- Integration with your identity, logging, and audit stack
- A handover your own team can operate
Software, accelerated
Ordinary software, unusual speed
Deterministic systems — the kind you would scope at two quarters — delivered in weeks, because our pipeline was designed after AI existed.
Engineers direct fleets of coding agents; evaluation harnesses do the checking humans used to do by sampling; humans hold architecture and judgment. Nothing about the output is exotic: typed code, tests, documentation, boring to operate. The speed is the only unusual part, and we do not charge by the hour, so it is not our problem to slow down.
For teams that need real software sooner than a traditional vendor can schedule a kickoff.
What you receive
- Production software with tests and documentation
- The delivery pipeline artifacts — you see how it was built
- A codebase your team can own without us
Value mapping
Where AI is worth it
A short, paid engagement answering two questions: where would AI produce the most value in your operation, and what has to be true for the risk to be acceptable.
We map your workflows, rank the candidates by value against risk, and scope the top of the list to the point where anyone could build it. Some of the honest answers are “not yet” and “not AI” — you get those too. The deliverable is a build order, not a deck: every item scoped, sequenced, and buildable by us or by anyone you choose.
For leadership that wants a defensible answer before committing a budget.
What you receive
- A ranked map of AI candidates in your operation
- Risk conditions stated per candidate, in plain terms
- A build order anyone competent could execute
Not sure which you need?
That is exactly what a discovery phase answers — fixed fee, 1–2 weeks, useful even if it ends there.
