Keep your production AI system boring.
You shipped it. Now it has to keep working at 10x the traffic, on next quarter's model, without a 2am page. That's a different job from building it — and the one most teams underfund.
Everything you need.To stay boring.
No vanity dashboards. No assumed quality. Real numbers, gated changes and a reliability floor — so the system holds at 10x and the bill stops climbing.
A telemetry dashboard you own
Live cost, latency (p50/p95/p99), error and fallback rates per AI feature. You stop guessing about your own system.
An AI bill that stops climbing
Cost-per-request and cost-per-outcome tracked and driven down — or held flat as volume grows — with every optimization documented.
Quality measured, not assumed
An eval suite that gates every prompt and model change, plus sampled live scoring, so drift is a caught number instead of a customer email.
Model upgrades that don't break you
When a provider deprecates or releases, we re-run evals and ship the swap behind a flag — no quality regression, no scramble.
A reliability floor
Fallbacks, retries, graceful degradation, an on-call runbook, and a postmortem after every incident. Fewer pages, faster recovery.
Headroom proven before you need it
Load-tested capacity numbers and an infra and quota plan sized to where you're going, so the next 10x is a config change, not a rewrite.
How we work.Audited, then operated.
Five steps from a cold production audit to a system that runs on a cadence — with real numbers before we touch anything.
A senior engineer reviews the live system: what's instrumented, cost-per-request, latency profile, eval coverage, failure modes, deprecation exposure. You get a written findings doc with risks ranked. We'll audit a system we didn't build.
We stand up the observability and eval harness so there are real numbers before we change anything. You can't claim a 40% cost cut without the baseline. This lands in days, not weeks.
We close the ranked risks from the audit — fallbacks, retries, the eval gates, the runbook, the obvious cost wins. The goal is to stop the bleeding and make incidents rare and recoverable.
Monitoring is live, evals gate every change, model upgrades are handled as they come, and a monthly review shows the telemetry, what shipped, and the next backlog. The SLA is in force.
We keep driving cost-per-outcome down, hold latency as volume grows, and load-test ahead of known growth events. If you want to take operations in-house, the handover is part of the deal.
We're not for everyone.We’re for teams ready to keep it boring.
If any of these sound familiar, we should talk.
We built it and now it's eating us
An LLM feature live, with no controls behind it
- A bill that climbs every month
- Latency that's a mystery
- Quality complaints arriving from customers
Outcome: A system you can see, priced and held under control.
You built it, keep running it
Shipped with us, one or two systems to maintain
- No wish to hire a full AI ops team
- Only one or two systems to keep alive
- Wanting the same engineers who scoped it
Outcome: Operation handed back to the team that built it, no new hires.
It can't survive the growth coming
A launch, a market or 10x users ahead
- A system that's fine today
- A growth event that will break it
- No headroom proven for what's coming
Outcome: The next 10x handled before it arrives, not during the outage.
Senior engineers. No handovers. No fluff.
Start your deployment.
Talk directly to a principal engineer.
No sales team.
No discovery workshops.
No procurement circus.
We scope, build and ship.
- Reply within 24h
- Engineer-led assessment
- Written proposal
- Portugal / EU timezone
No commitment. Just an engineer.