Overview
An AI system is not finished when it launches. Its behaviour shifts as the data around it changes, providers release new model versions, costs move with usage, and the operation keeps changing what it asks of the system. Managed AI Operations keeps it working after the launch date.
We run what we ship. Every system under management is monitored for availability, errors, response times and cost, and every model call is logged with the model used, its cost, its confidence and the outcome. Evaluation sets are re-run on a schedule and after every change, so drift is caught by a test rather than reported by a customer.
When something breaks, an on-call engineer responds under the terms of a service level agreement, with runbooks for known failures and a written review after every incident. Our delivery and support team in Thailand works alongside engineering in the United States.
Capabilities
Monitoring and on-call
Availability, errors, response times and usage monitored continuously, with alerts routed to an on-call engineer and runbooks for known failures.
Model evaluation and drift
Evaluation sets re-run on a schedule and after every change, so a drop in quality is caught by a test and investigated.
Updates and patching
Models, dependencies and infrastructure kept current, with every change tested against the evaluation harness before it reaches production.
Cost management
Every model call attributed to the system and team that made it, so AI spend is visible and can be controlled.
Incident management
Incidents contained, communicated and followed by a written review that records the cause and the fix.
Service level agreements
Response times, availability targets and reporting agreed in writing, with regular reports against them.
Audit reviews
Scheduled reviews of the decisions a system made, so issues surface on a regular cadence instead of only after an incident.
Technical detail
Industries
Questions
- Can you operate a system Opsian did not build?
- Yes, after a review. We assess the system, fill gaps in monitoring, evaluation and documentation, and then take it under management.
- How do you know a model has drifted?
- Its evaluation set is re-run on a schedule and after every change. A drop in scores raises an alert, and the cause is investigated before more users are affected.
- What does the service level agreement cover?
- Response times, availability targets and reporting, agreed in writing for each system before it comes under management.
More services
- 01AI DefenseAI securityProtection against prompt injection, data leakage and model abuse, with red teaming, AI governance and monitoring, and AI-assisted threat detection across your systems.
- 02Cyber SecuritySecuritySecurity assessments, identity and access control, monitoring and incident response for the systems that hold identities, payments and operational data.
- 03ConsultingAdvisoryStrategy, architecture and governance advice for leadership teams, starting with an audit delivered as a document you own and are free to take elsewhere.