Run: Governance, Risk & Operations
AgentOps & Managed AI Operations
Run agents in production: monitoring, evaluation drift, guardrails, incident response, cost control, and model lifecycle — under an SLA.
Agents run continuously, and their quality, cost, and risk drift. AgentOps is our managed service for production AI systems: observability, continuous evaluation, guardrail tuning, incident response, FinOps, and model lifecycle management, reported monthly against an SLA.
Who it's for
- Operations and platform teams running agents without a dedicated AI ops function
- CFOs watching inference spend
- Risk leaders who need continuous evidence, not annual audits
What you get
How it works
-
01
Onboard
Instrument systems, baseline quality and cost, agree SLOs.
-
02
Operate
Monitor, evaluate, respond, optimise.
-
03
Report
Monthly scorecard: reliability, quality, cost, incidents.
-
04
Improve
Quarterly roadmap for autonomy increases and cost reductions.
Proof
Technical notes
Tracing with OpenTelemetry; online evaluation sampling with LLM-as-judge and human review queues; drift detection on input distributions and output quality; per-agent cost attribution with budget alerts; model gateway policies for fallback and routing.