03 · Run — AI-Enabled Ops
Operations that increasingly run themselves.
Put detection, diagnosis, and routine fixes on autopilot — so issues get caught before they page anyone, alert noise drops, and cloud costs stay honest. Your engineers stay on the decisions that need judgment.
The problem
As estates grow, keeping them alive becomes a tax: noisy alerts, 2am pages for things that could self-heal, dashboards nobody reads, and a cloud bill that creeps every quarter. More headcount isn't the fix — better-instrumented, AI-assisted operations are. This is the intelligent layer on top of the NOC, Ops, and FinOps we already run for clients.
What we do
AIOps & intelligent observability
Correlate logs, metrics, and traces; surface the signal; detect anomalies before they become incidents; query telemetry in plain language.
Self-healing & automated remediation
Codified runbooks that trigger on detection, with guardrails and approvals where it counts. Routine fixes happen without waking anyone.
AIOps for the NOC
Alert correlation and noise reduction layered onto NOC as a Service and Operations as a Service, so on-call sees real incidents, not a wall of pages.
MLOps & LLMOps
Deploy, evaluate, and monitor models and LLM features in production: drift detection, evals, guardrails, and cost governance for AI workloads.
Agentic ops automation
Agents that triage alerts, enrich tickets, and draft incident updates as an on-call copilot — under human oversight.
AI-driven FinOps
Continuous cost-anomaly detection and forecasting on top of Cloud FinOps, so spend tracks usage instead of drifting.
Outcomes
MTTR ↓
Issues detected and often resolved before they escalate.
[MTTR ↓ — confirm]
Noise ↓
Alert noise cut so on-call focuses on what's real.
[noise ↓ — confirm]
Spend ↓
Cloud and AI spend tracked and trimmed continuously.
[spend ↓ — confirm]
Uptime ↑
Higher uptime with a smaller on-call burden.
[uptime — confirm]
How it fits
AI-Enabled Ops is the intelligent evolution of Managed Services & Operations. It layers directly onto NOC as a Service, Operations as a Service, and Cloud FinOps, and draws on AI & Generative AI from Data, AI & Security. It's also how we operate the products we build under Product & Application Engineering — so you're not inheriting something we wouldn't run ourselves.
Curious what “on autopilot” would look like for your estate?
Bring a sketch, a spec, or just a problem. We'll come back with an approach, an architecture, and a number you can plan around.