Managed operations
Keep the system working for you.
Support, workflow tuning, access reviews, and model or tool updates after launch.
We stay involved after deployment. Your team and ours look after the system together, from the first support call to the next model update.
The work that continues after launch
- Support
- System support, documentation and user adoption.
- Improve
- Search quality and workflow changes, informed by the people using them.
- Review
- Access, governance and approved updates.
- Extend
- New data sources and workflows, assessed before the system grows.
Models drift.
An AI system is not static software. Data shifts and new cases appear. Without oversight, it degrades.
- Scheduled tests
- Run against known answers, for accuracy and safety.
- Drift
- Questions and answers watched for the moment they move outside what the model was built for.
- Checked answers
- Outputs compared with your trusted records.
- Feedback
- A simple way for people to flag a wrong answer, fed back into improvement.
Five planes, one system.
A choice made for cost changes what the infrastructure can carry, and the quality of the data decides how far anyone can trust the answers. We keep all five in view.
- FinOps
- Technology spend aligned with financial governance and cost control.
- DataOps
- Governed data pipelines that keep analytics and AI reliable.
- DevOps
- Standard deployments, environments, observability and release control.
- MLOps
- Monitoring, evaluation, model serving and lifecycle control.
- SecOps
- Security, compliance, identity, evidence and threat detection.