Training gets a team ready. Sometimes the harder problem is the first system — the one that has to work on real data, survive a security review and still be maintainable in a year. We build those alongside your engineers and hand them over properly.
All of it scoped narrowly enough to ship. We'd rather deliver one automation your team trusts than a platform nobody uses.
The tools your team keeps asking for and nobody has time to build — document handling, reporting and the spreadsheet that has quietly become critical infrastructure.
Agents scoped to a job with a clear boundary, a clear escalation path and enough tracing that you can explain any individual decision afterwards.
Nothing useful lives in isolation. We connect the system to your existing services through MCP or plain APIs, with authentication and permissions handled properly.
We build alongside your engineers and train them as we go. The engagement ends with your team owning the system, the tests and the runbook.
You can stop after any stage with something of value in hand. That's deliberate — it keeps the incentive on shipping rather than on extending the engagement.
A short paid discovery: we look at the workflow, the data and the constraints, and tell you plainly whether AI is the right tool for it.
Two to three weeks to a working prototype on real data, so the decision to continue is made on evidence rather than a slide deck.
Hardening: evaluation suites, tracing, cost ceilings, permissions and the failure paths. Built with your engineers, not for them.
Your team takes ownership with documentation, a runbook and a training day. We stay available, but you don't need us.
These go into the statement of work, because they're the things that decide whether a system is still running eighteen months later.
Running a track in parallel with the build is the difference between a system your team inherits and one they helped design. Pick the track that matches what we're building.
Discovery is short and paid, and it ends with an honest answer — including 'this doesn't need AI', which is the answer more often than the industry admits.