Cloudaeon AI Hub - A production control system for enterprise AI

AI Hub: A Production Control System for Enterprise AI

AI Hub gives every AI use case one governed, repeatable route from idea to live production. It runs in your tenant, on the stack your teams already use, bringing together business ownership, approved model and tool access, validation evidence, gated release and one operational trace across Microsoft and Databricks.

AI Hub does not replace Microsoft, Databricks or your AI development environment; it adds a consistent lifecycle and control model around their native capabilities.

The Challenge

The gap is not the model. It is getting one serious AI use case live, governed and kept running. Enterprises face fragmented delivery, governance added late, limited visibility of what is running, operational risk, and difficulty understanding AI usage and cost.

AI Hub addresses this with a governed production path that connects business ownership, engineering, governance and operations.

One Governed Path for Every AI Use Case

AI Hub provides a seven-stage lifecycle:

1. Register – Capture the use case, owner, expected value, data and risk.
2. Configure – Define approved models, policies, guardrails, limits and approvals.
3. Provision – Establish governed access, environments, secrets, APIs and monitoring.
4. Implement – Build applications, agents, RAG solutions or workflows using the existing technology stack.
5. Validate – Bring evaluation results, thresholds and human sign-off together as production evidence.
6. Promote – Check evidence and approvals and govern the production release decision.
7. Operate – Capture usage, cost, traces, failures, drift, feedback and audit history.

One governance and evaluation trace runs beneath the lifecycle, linking ownership, configuration, policy, evidence, evaluation and approvals to the same use case.

Governed by Default

AI Hub enforces controls where it owns the control point and observes where native platforms remain authoritative.

Controls can include use-case approval, approved configuration, gateway authentication, permitted models and tools, usage limits, validation evidence and human approvals.

Operational visibility includes usage, cost per use case, evaluation results, drift, guardrail events, policy breaches, failures, latency, feedback and release history.

Technology & Integration

AI Hub works with the customer's existing technology environment, including Azure AI Foundry, Azure OpenAI, Microsoft Fabric, Copilot Studio, Databricks and custom applications.

Enterprise data access remains governed by native Microsoft and Databricks permissions. Identity uses Entra ID and native platform identity. AI Hub can use Foundry and Databricks/MLflow traces and is deployed within the customer's tenant.

Supporting Microsoft Azure Adoption

This professional services engagement helps customers get started with or extend their use of Microsoft Azure by establishing a governed foundation for enterprise AI within their own tenant.

Cloudaeon works with customer teams to define the first governed AI use case and establish the governance, access, monitoring, validation and operational controls required to move it toward production.

For customers already running AI solutions on Microsoft Azure, existing applications can be brought under the same governed lifecycle, policies, evaluation and trace without requiring them to be rebuilt.

How We Engage

Discover – Define the first governed AI use case, owner, outcome, current gaps and implementation scope.

Production Setup – Deploy the governed path in the customer's tenant and release the first use case through the agreed lifecycle.

Run – Operate and improve production AI across cost, quality, evidence and operational performance.

AI Hub provides the governed foundation. Customer teams build on it, while Cloudaeon's Data, Cloud, AI and Operations specialists can help build, run and expand production capability.

Who It Is For

AI Hub is designed for enterprises and public-sector organisations adopting or scaling AI, including financial services, retail, healthcare, manufacturing and technology organisations.

Typical stakeholders include AI and platform teams, governance and risk teams, enterprise architects, technology leaders, business sponsors and cost owners.

Value Proposition

From pilot to production: governed, repeatable and yours.

AI Hub provides one governed route to production with visibility across ownership, policy, evidence, cost, evaluation, operational performance and audit history.

Get Started

Bring one AI use case. See AI Hub on a live use case — from pilot to governed production.