AI operations integrations and automations

Running agents and models in production, with the cost attributed, the tools scoped, and every run joined to the work it actually did.

Running a model in production is mostly not a model problem. It is knowing what an agent did, what it was allowed to do, what it cost, what it was allowed to read, and whether the answer it gave was right. The recurring design decision is what to gate on: blast radius rather than model confidence, coverage rather than a score, and the outcome rather than whether the run threw an error.

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