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After a Production Build
Most clients move into Operations the month their system goes live, whether we built it or another team did. We assess what's deployed, learn how it should work, and take over the engineering ownership.
Your AI systems and agents stay sharp in production. We run them, monitor them, and improve them every month. Behavior evals, context upkeep, guardrails and audit trails, model upgrades. The discipline that makes AI compound in value instead of decay.
Trajectories and outcomes, not just outputs. Running continuously, so we see degradation before your users do.
When something breaks, we're the first call. Not your engineering team's pager.
The knowledge, tools, and instructions your agents run on, kept in sync with how the business works today. Versioned and reviewed.
Per-use-case spend tracking. Budget caps and alerts before invoices surprise. Model and vendor decisions logged for audit.
What your agents may do on their own, what escalates to a human, every action logged. EU AI Act obligations tracked as they take effect.
New models ship every month. We re-test, swap what wins, and your system gets sharper with no rebuild.
We ship new capabilities, not just keep the old ones running.
We sell the engineering discipline that makes AI systems compound in value instead of decay.
Most clients move into Operations the month their system goes live, whether we built it or another team did. We assess what's deployed, learn how it should work, and take over the engineering ownership.
You shipped something months ago. Nobody knows if it's still performing the way it did at launch. Drift, broken integrations, quiet degradation. We do an initial assessment, then take over operations.
Your AI runs. Your team maintains it. But monitoring is ad hoc, evals are inconsistent, context goes stale, and new models ship without anyone re-testing. You don't need rescue. You need engineering discipline at production-grade. We bring it.
If your AI doesn't yet run in production, you're looking for Production Build, not Operations.
We start with an initial assessment to learn what's deployed and where the risks are. Then we take over engineering ownership: monitoring, evals, runbook, governance. Most clients see meaningful improvements in the first month.
Monthly retainer scoped to your system complexity and response SLAs. After a 30-minute call we send a clear proposal. No usage-based surprises.
Per-use-case spend tracking, budget caps, alerts before invoices surprise. Vendor and model decisions logged for audit. We watch cost-per-outcome, not just cost-per-call.
Yes. AI Operations works alongside your team, not instead of them. We bring the discipline (evals, monitoring, cost governance, model risk reviews) so your team can ship the next thing instead of firefighting the last.
30-minute call. We'll walk through what you've deployed, how it's currently being maintained, and where we'd add value. Straight answer either way.
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