Simor Managed Operations
Ongoing operation and monitoring of production AI systems.
Day-2 operations — because deploying AI is the easy part. Running it reliably is the hard part.
24/7
On-call coverage
35%
Average cost reduction achieved
<5min
Mean rollback time
01 Capabilities
What this division does
AI observability
Dashboards and alerting covering the metrics that matter for AI: token economics, latency distributions, error taxonomy, and output quality signals — not just uptime.
Evaluation operations
Continuous evaluation pipelines that run regression suites on every model change, with automated quality gates that block deployments when scores drop.
Incident response
On-call coverage with AI-specific runbooks: degraded model quality, provider outages, cost spikes, guardrail failures. We treat AI incidents as a distinct operational discipline.
Cost control
Budget alerting, per-route cost attribution, and anomaly detection that catches runaway spending before it hits the invoice. Token economics is a first-class operational concern.
02 Approach
How this division works
AI systems fail differently than traditional software. Quality degrades gradually, not just hard. We monitor output quality distributions, not just error rates.
Every model change is a canary. We deploy behind feature flags with automated quality gates and rollback if regression suites fail.
Runbooks are living documents. We write them during incidents while context is fresh, not afterward from memory.
03 Use cases
Where this division delivers
24/7 AI platform operations
Managed observability, incident response, and continuous evaluation for a production AI platform serving millions of requests. SLO enforcement with automated escalation and quarterly quality reviews.
Cost optimisation programme
Per-route token attribution, provider cost benchmarking, and routing optimisation that reduced monthly LLM spend by 35% while maintaining output quality.
Model migration operations
Managed canary deployment of a new model version with automated regression testing, quality gates, and instant rollback when a 2% quality dip was detected in production traffic.
04 Lifecycle
Position in the lifecycle
Simor Group covers the full AI infrastructure lifecycle. This division operates at the Operate stage.
05 Services
Full service list
- Managed observability for AI systems (latency, token usage, error rates)
- Evaluation operations (continuous eval, regression detection)
- Incident response and on-call coverage
- Cost anomaly detection and budget alerting
- Model-change testing and canary monitoring
- SLO definition and enforcement
- Runbook authoring and maintenance
07 Engage
Work with Managed Operations
Tell us about your system, your timeline, and your constraints. We will come back with a scoping conversation — not a sales pitch.