Operations & Reliability
Take your AI from PoC stuck in dev to a production system your team can operate.
We come in when your AI works in a notebook but stalls on the way to production. Or when it's in production but drifting, expensive, or fragile. We do the engineering you need to make it boring.
What we ship
Concrete deliverables, not features.
01
PoC-to-production engineering
Take a working prototype and ship it as a maintainable production system. Containerization, deployment, observability, cost controls, eval suite, runbook for your team.
02
Existing system stabilization
Audit and re-engineer AI systems in production that are unreliable, expensive, or hard to extend. Pragmatic fixes, not rewrites for their own sake.
03
Evaluation infrastructure
Eval suites, regression tests, observability dashboards. The instrumentation that lets your team ship AI changes without flying blind. Hosted on your stack, runs in your CI.
04
Operations retainer
After delivery, a monthly retainer to keep the system healthy: monitor drift, manage costs, roll out improvements, handle incidents. Quarterly review against business outcomes — no auto-renew.
How it works
Discovery first. Weekly cycles. Pause anytime.
- Discover01
Discovery sprint
Two weeks, fixed scope. Working prototype on your data, architecture decision record, scoped follow-on proposal.
- Design02
Operate
Weekly cycles with demos and decision points. Scope can be adjusted, paused, or ended after any cycle. No surprises at the end.
- Build03
Ship to production
Code in your repositories. Deployment in your cloud by default. Runbook written for your team to operate, monitor, and extend it.
- Operate04
Optional retainer
Monthly retainer to maintain, monitor, and extend the system. Quarterly review against business outcomes. No auto-renew.
Where it compounds
Scenarios where this work pays back.
01 · Use case
Stuck PoC with engineering debt
A notebook prototype that works in dev. You need it in production but the team doesn't have the time or specific experience. We do the engineering, hand over the runbook.
Typical engagement: 6–12 weeks, ending with a production deployment your team can extend without us.
02 · Use case
Production AI that's expensive or drifting
System in production but the bills are climbing, quality is degrading, or you can't ship improvements without breaking things. We diagnose, stabilize, instrument, then optionally retainer.
Typical first sprint: 3–6 weeks of stabilization, with observability + eval gates in place by end.
03 · Use case
Ongoing operations for systems we built
Most clients who shipped a custom system with us continue on a retainer for operations: monitoring, cost management, incident response, model upgrades, capability extensions.
Monthly retainer with a quarterly business-outcome review, no lock-in.
Engagement
Fixed scope after discovery.
- Duration
- 2–4 months initial, retainer ongoing
- What you get
- Production-ready system, eval suite, runbook, optional retainer
- Start with
- Discovery sprint, 2 weeks
Frequently asked
Questions before the first call.
We have a PoC built by another vendor. Can you take it over?
Yes — we do this regularly. We start with a 1–2 week audit (separate engagement) to understand what was built, what works, and what needs to be re-done. Then a stabilization sprint with a clear handover plan.
What does a typical retainer look like?
Defined scope per quarter (e.g., 'monitor system X, ship 1–2 improvements per month, handle incidents within Y SLA'), measured against business metrics agreed upfront. Quarterly review, both sides can end with one cycle notice. No auto-renew.
How do you bring down AI costs in production?
Profile first — which interactions cost what. Then routing (cheap models for easy cases, expensive for hard), caching, prompt-engineering token efficiency, batching where latency allows, and sometimes fine-tuning a smaller model. Typical reduction: 3–10×, depending on starting point.
Will you train our team to operate it themselves?
Yes — that's the default goal. Runbook, observability handover, a 2–3 week shadowing period where your team operates and we're on call. After that, you decide whether to retainer with us or run it internally.