Services 04
Someone responsible for the system after launch.
For teams with an AI system that works today and no one watching it tomorrow.
In plain terms
A system in production changes under you: the model provider updates, your data drifts, users ask new things. We watch the system, score a weekly sample against your evaluation set, fix what real usage breaks, and send a report every month that a non-engineer can read in ten minutes. We do this for systems we built and for systems we did not.
Running systems in production
How it fits together
- SystemYours or ours, in your cloud.
- LogsEvery request and answer, kept private.
- EvaluateA weekly sample scored against your set.
- AlertDrift, cost and errors raised early.
- FixPrompts, retrieval and rules adjusted.
- ReportOne page a month, in plain language.
What you receive
- Phase 1
An audit of the existing system: evaluation, logging, cost and failure modes.
- Phase 2
An evaluation set written with your team, if there is none.
- Phase 3
Monitoring and alerts inside your cloud.
- Phase 4
A monthly report with the trend, the incidents and what changed.
Related work
Systems we have shipped.
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