How we work

People-led, AI-powered.

We don’t hand you a model and wish you luck. Senior practitioners embed with your team, build the deterministic system, and leave you owning the capability.

Who
Senior ML practitioners
How
Embedded, on your systems
Done when
You don’t need us
The engagement

From a process you can describe to a capability you own.

  1. Write down the steps

    We start where you do: the actual procedure. If a process can be specified, it shouldn’t be left to a model to guess at runtime.

  2. Bound the intelligence

    We isolate the few points that genuinely need human-like judgment. Everything else stays deterministic — testable, loggable, repeatable.

  3. Build it deterministic

    We author the YAML workflow and MCP integrations against your real systems, on your network. No re-platforming, no data egress.

  4. Prove it

    Execution trails, reproducibility, and audit from day one — so the result holds up to scrutiny, internal or regulatory.

  5. Hand over ownership

    We train your team to run, extend, and own the capability. The engagement is finished when you no longer need us.

Training & enablement

We’d rather make you independent.

Ownership is the point. We train your people to operate, build, and reason about deterministic AI — so the capability outlives the engagement.

01

Operator training

Run, monitor, and trust SACER workflows in production — reading execution trails and handling edge cases.

For operators
02

Builder training

Author and extend workflows in YAML and wire MCP integrations to your own systems.

For engineers
03

Judgment design

Decide where intelligence belongs — and, more often, where it doesn’t.

For leads

Bring us a process you can describe.

If you can write down the steps, we can probably make them deterministic.

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