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Common Questions

We’ve gathered the most frequent questions about AI Fabrix — from setup to security. Explore the Q&A or start a free trial now.

FAQ’s

Frequently Asked Questions

What is AI Fabrix?
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AI Fabrix is an Azure-native, in-tenant enterprise AI platform that enables secure, governed AI adoption at scale.
It turns fragmented enterprise systems into permission-aware, AI-ready data using open standards—so AI agents, workflows, and applications can run safely in production, not just pilots.

What are the system requirements?
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AI Fabrix runs entirely inside your Azure tenant and uses standard Azure services for compute, storage, networking, and identity.
There is no shared SaaS component and no external service accounts. Infrastructure sizing depends on workload and scale, and follows a predictable, infrastructure-based model.

Is AI Fabrix secure and compliant?
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Yes. Security and governance are foundational to AI Fabrix. All data and AI operations run inside your Azure tenant, using Entra ID for identity, ABAC/RBAC for access control, and full audit logging for every data access and AI action. This enables compliance with enterprise and regulated-industry requirements.

How do I get started with AI Fabrix?
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Most customers start with a guided deployment inside their Azure tenant. This includes setting up governance with Miso, connecting core systems through CIP, and deploying an initial AI agent or use case. From there, teams expand incrementally using the same governed foundation.

Can I integrate AI Fabrix with existing systems?
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Yes. AI Fabrix integrates with enterprise systems using OpenAPI and Composable Integration Pipelines (CIP).This approach avoids custom SDKs and service accounts, automatically enforcing identity-based access (ABAC/RBAC) and providing full metadata, lineage, and auditability across systems such as CRM, ERP, HR, Finance, SharePoint, and custom APIs.

What support options are available?
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AI Fabrix offers documentation, reference architectures, and enterprise support options.
Customers also receive guidance on governance setup, integration patterns, and production rollout to ensure AI moves safely from pilot to scale.