In-tenant. Azure-native. Governed by design.
AI Fabrix runs entirely inside your Azure tenant, using your identity, network, and security boundaries.
CIP enforces identity and policy at the dataplane boundary, before data ever reaches AI.

AI Fabrix is an enterprise AI control and execution fabric that runs entirely inside your Azure tenant. It extends Microsoft’s cloud and AI services with the governance, identity, and environment control required to move AI from pilots to production — safely and predictably.
Unlike external SaaS AI platforms, AI Fabrix does not copy data, bypass identity systems, or introduce hidden control planes. All AI agents, workflows, and integrations operate using your existing Azure infrastructure, Entra ID identities, and security boundaries.
At the center of the platform is Miso Controller — the enterprise control plane that governs identity, access, environments, policies, and audit across all AI workloads.

Miso Controller is the governance layer of AI Fabrix. It separates control from execution, ensuring that AI runtimes remain lightweight while all enterprise rules are enforced consistently.
Miso centrally manages:
This allows AI to operate under the same identity, permission, and compliance rules as human users — without duplicating RBAC logic across tools.
AI Fabrix introduces an environment-first authorization model designed for enterprise delivery.
Applications define their roles and permissions once. Miso binds those roles to enterprise identity groups per environment, allowing different access levels in Development, Test, and Production.
This enables:
—all without rewriting access logic or maintaining separate identity models per tool.
AI Fabrix integrates with enterprise identity providers using open standards:
AI Fabrix enables AI to perform real enterprise actions — safely.
AI agents cannot directly modify enterprise systems. All write actions are routed through Miso’s governed execution layer, where permissions are evaluated and every action is logged.
This ensures:
AI doesn’t bypass governance — it enforces it.
AI Fabrix enables attribute-based access control (ABAC) using business metadata.Labels derived from CRM, collaboration, and HR systems are used to enforce permission-aware retrieval across documents and vectors. AI responses are generated using only the data the user is allowed to see — in context.
This enables safe, explainable Retrieval-Augmented Generation at enterprise scale.
AI Fabrix is designed for production deployment, not experimentation.
What works in pilot works in production — without redesign.
Every AI action is logged, auditable, and traceable.
AI Fabrix aligns with ISO-27001 principles and supports regulated industries by providing centralized audit logs, policy decision tracking, and environment-level observability — all inside the customer tenant.
Open Standards. No Lock-In. Full Control.
AI Fabrix is built on open, proven standards such as OpenAPI, OIDC, SCIM, and MCP. Customers retain full ownership of their infrastructure, data, and exit strategy — always.

Control Plane — MisoCIP
Controls who can do what, where, and under which policies:
Dataplane — CIP + Retrieval
Supplies governed, contextual data to AI:
Orchestration — Microsoft Copilot, Flowise
Orchestration — Microsoft Copilot, Flowise
Enterprise UX — Microsoft Copilot, OpenWebUI
How a Typical Request Flows
1. Identity Is Established First
2. Policy Is Evaluated Centrally
3. CIP Supplies Data, Not Systems
4. Retrieval Is Permission-Aware
5. Response Is Governed by Design
Microsoft delivers powerful AI services such as Microsoft Copilot, Azure OpenAI, and Azure AI Search. These are essential building blocks — but by themselves, they do not provide the full enterprise AI fabric.
AI Fabrix is not a competitor to Microsoft. Instead, it complements Microsoft by adding the missing enterprise control layer: governance, metadata-aware retrieval, and predictable economics — all running in your own Azure tenant.

- Copilot is user-facing: It provides productivity features inside Office, Teams, and Dynamics, but it is limited to those applications.
- Fabrix is platform-level: It governs, orchestrates, and secures all enterprise AI workloads across Microsoft 365 and beyond.
This distinction allows enterprises to use Copilot for personal productivity while relying on Fabrix for governed, organization-wide AI adoption.
Many CIOs report that using Copilot alone requires a lot of manual work:
- Custom connectors must be coded and maintained separately.
- Compliance, audit, and quota enforcement are missing.
- No central governance across AI pipelines.
- Cross-system knowledge retrieval needs heavy custom development.
Fabrix fills these gaps out of the box, turning Microsoft’s AI services into an enterprise-ready platform.
AI Fabrix enables enterprises to build secure, policy-aware AI solutions on top of Microsoft services. Its in-tenant design, metadata-aware retrieval, and governance features make it ideal for scenarios where compliance and business value must go hand in hand.

Fabrix integrates with SharePoint, Teams, and OneDrive to deliver permission-aware retrieval. Users only access the documents and messages they are entitled to, reducing compliance risks.
This allows organizations to create internal knowledge assistants that scale across departments while maintaining security and access integrity.
OpenWebUI provides a space for teams to build cases collaboratively. Users can attach evidence from SharePoint, Teams, CRM, or ERP systems, while Fabrix enforces audit logging and access controls.
This turns conversational AI into a secure workspace for compliance-driven processes like investigations, audits, and legal reviews.
Unlike generic chatbots, Fabrix enables the creation of assistants with built-in policy enforcement. These assistants apply enterprise rules to every interaction, ensuring outputs comply with governance, security, and regulatory standards.
They are particularly valuable in regulated industries such as finance, healthcare, and the public sector.
Fabrix can support sales and delivery teams by creating workspace assistants linked to deals or projects. These workspaces aggregate documents, meeting transcripts, and evidence, making it easier to collaborate and prepare business cases.
Integration with CRM systems ensures that AI-powered insights are contextualized and policy-aware.

This diagram shows the contrast:
Generic chatbots answer questions but lack governance, policy, or compliance guarantees.
Fabrix use cases are structured, governed, and directly tied to enterprise processes.
AI Fabrix extends Microsoft 365 and Azure with enterprise-ready AI use cases that are secure, policy-aware, and directly tied to business outcomes.
By combining metadata-aware retrieval, governance enforcement, and collaborative workspaces, Fabrix moves AI adoption beyond pilots and into production-grade solutions.
This sequence shows why AI Fabrix scales safely:
This is the difference between using AI and deploying AI at enterprise scale.
Traditional Enterprise AI Stacks vs AI Fabrix.
The difference between AI Fabrix and traditional stacks is not capability.It is where failure modes are allowed to exist.
Traditional stacks allow failure by design.AI Fabrix removes failure structurally.
1. Identity Loss
What breaks traditionally
Why Fabrix holds
2. Permission Leakage
What breaks traditionally
Why Fabrix holds
3. Governance Drift
What breaks traditionally
Why Fabrix holds
4. Audit Reconstruction
What breaks traditionally
Why Fabrix holds
5. Service Account Sprawl
What breaks traditionally
Why Fabrix holds
6. AI Exception Paths
What breaks traditionally
Why Fabrix holds
7. Integration Fragility
What breaks traditionally
Why Fabrix holds
8. Platform Sprawl
What breaks traditionally
Why Fabrix holds
Traditional stacks fail because they allow failure to exist:
AI Fabrix succeeds because those failure modes are removed by design.
This is not an implementation choice.It is an architectural one.
Traditional AI stacks ask teams to avoid failure.
AI Fabrix makes failure structurally impossible.