Keep the solution useful after the first release.

AI-enabled systems need attention as models, data and business processes change. We can provide an agreed support and improvement programme covering integrations, answer quality, usage costs and releases. Where information or infrastructure requirements call for a different setup, we assess dedicated hosting and private AI options as part of the design.

Discuss ongoing support
Illustrative

What this can include

  • Maintenance and connector monitoring

    Monitoring and maintenance for the integrations in the agreed support scope, with incident handling and responsibilities defined.

  • Regression evaluations

    Model or prompt changes tested against reviewed examples before they reach anyone.

  • Quality improvements

    Answers improved using what people actually ask and where results fall short.

  • Usage reporting and cost controls

    Usage made visible and model costs kept within agreed limits.

  • Dedicated and private deployments

    Dedicated hosting or private AI assessed where your information or infrastructure requirements call for it.

Illustrative workflow

A controlled model change

  1. A model change is proposed for a workflow in the support scope.

  2. The current version provides a baseline on reviewed examples.

  3. The proposed version is tested against the same examples.

  4. Its results are compared with the current version.

  5. The change is rolled out only after the agreed checks pass.

What you get

  • An agreed support and improvement programme
  • Monitoring and incident handling for integrations in scope
  • Evaluation suites and release checks
  • Usage and cost reporting
  • Recovery planning

Integration and data considerations

  • Support hours, response targets, hosting and retention are agreed in the contract.
  • Whether a local model is suitable depends on the capabilities you need.
  • Private deployment covers the complete data path, not just where one application runs.

How people stay in control

  • Upgrades are controlled and tested before release.

  • Provider selection and data handling are specific to your project.

  • Private deployments are scoped projects, not instant self-service plans.

Questions about managed ai and private deployment

Do you offer 24/7 support?

Support hours and response targets are agreed for each engagement. We don’t advertise a standard round-the-clock service.

Can everything run on our own servers?

Sometimes. We assess the complete processing path and the capabilities you need before recommending private hosting or local models.

Discuss ongoing support.

Describe the process, the systems involved and where the work gets stuck. You don’t need a finished technical brief.

Discuss ongoing support