Managed AI Services

Keep your AI working as the business changes.

Put a defined operating plan around your AI applications, model deployments and integrations, with clear responsibilities for maintenance and improvement.

Scope your managed AI service
SERVICE REVIEWHealthEvaluationCostReviewsHealthNamed services and alert reviewOperating reviewsCoverage and escalationApproved changesNext improvement steps
Example interface
Illustrative view of AI service health and operating reviews

Support for the complete service.

We manage the application, model-serving environment and integrations covered by your service plan. Monitoring, incident handling and controlled releases keep the operating responsibilities connected, while regular reviews identify where quality, capacity and cost can improve.

What our managed services cover.

  • Health monitoring, alert review and incident triage.
  • Dependency maintenance and approved security updates.
  • Model and prompt evaluation before changes.
  • Review of operator feedback and recurring exceptions.
  • Cost, capacity and usage reviews.
  • Backup and recovery checks where included.
  • Reporting on service performance, issues and planned improvements.

Coverage matched to your operations.

Choose business-hours, extended or round-the-clock support to match your operations. Your service plan defines coverage, response targets and escalation, alongside continuous monitoring and scheduled improvement work.

Clear provider responsibilities.

Infrastructure and model providers remain part of the service chain. We document what Oasis Gate manages, what the provider covers and what your organisation retains, including access, approvals and business decisions.

An operating plan you can review.

You receive a service catalogue, system inventory, responsibility matrix, contact and escalation plan, and agreed review cadence. Availability targets and response commitments apply to the named services and contracted coverage.

A model catalogue and managed endpoint workspace
Related experience

Enterprise AI Model Governance on Azure

A custom Azure-based LLMOps platform developed for a private equity firm to organise model usage across engineering projects through a managed endpoint gateway, model registry and discoverable catalogue.

Explore the project

Scope your managed AI service

Tell us what you want to deploy or improve. We will discuss hosting, integration and operational requirements.

Scope your managed AI service