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Services / 04 — Managed Services

We operate what we ship.

Most consultancies leave at go-live. We stay: managed AI operations, 24×7 platform operations, and cost control under real SLAs — run by the engineers who built the system, on AWS, Azure, or Google Cloud.

What organisations are asking
Who keeps the AI honest after go-live?

We do — with evaluation suites that run on every change, drift monitoring on live traffic, and guardrail tuning as your data and models evolve. An AI system without operations is a liability with a demo.

Can you take over a platform someone else built?

Yes. A two-week discovery sprint maps the estate, the risks, and the quick wins. You get the findings whether or not you engage us further — then onboarding into managed operations is measured in weeks.

What does an SLA look like for an AI system?

The same as for any production system, plus quality: availability and response-time targets, incident severities with response commitments, and measured answer-quality thresholds with an agreed process when they slip.

The practice

Three ways we deliver Managed Services.

M.01
AI Ops

Managed AI operations

Continuous assurance for systems that think: quality, safety, and cost of your AI workloads, managed as a discipline.

  • Evaluation suites on every model, prompt, or data change
  • Drift, quality, and safety monitoring on live traffic
  • Model and provider swaps as better options ship
  • Token-level cost tracking per workload
Put your AI under management →
M.02
Platform

Managed cloud platform

24×7 operations for your cloud estate — monitoring, patching, and incident response with the discipline of site reliability engineering.

  • 24×7 monitoring and alerting across your clouds
  • Patching, backup, and recovery on a published cadence
  • Incident response with severities and SLA commitments
  • Reliability engineering: error budgets, post-incident reviews
Hand over the pager →
M.03
Improve

FinOps & continuous improvement

A monthly engineering review — not a status call. Costs go down, reliability goes up, and the backlog of small improvements actually shrinks.

  • Monthly cost, reliability, and security review with actions
  • Right-sizing and reserved-capacity management
  • Continuous hardening against evolving baselines
  • Quarterly architecture health checks
Take financial control →
What good looks like
Accountability

One team from architecture to the 3am page. No hand-offs, no blame gaps.

Onboarding

Two weeks from discovery sprint to findings; weeks — not months — to full management.

Trajectory

Every month the platform is measurably cheaper, safer, or faster than the last.