What does FaburAI do?

FaburAI is an AI governance platform for the distributed AI estate. It discovers the AI agents, MCP servers, tools and data assets already running across an enterprise, models them in a canonical governance data model, and enforces access policy at the edge — down to individual data columns. Policy decisions execute inside the customer’s own environment.

Is FaburAI in the request path between agents and tools?

No. FaburAI publishes policy; enforcement runs inside the customer’s own environment, where every allow or deny decision is evaluated locally. Governed calls never leave the customer’s network to reach FaburAI. Because decisions are made locally, enforcement continues against the last known good policy even if FaburAI is unreachable.

How is FaburAI different from an AI gateway or MCP proxy?

AI gateways and MCP proxies enforce by sitting in the traffic path as an external service, so governed calls leave the customer’s network to be evaluated. FaburAI distributes enforcement instead: it produces policy, and enforcement happens at the edge inside the customer’s own environment. FaburAI also governs down to the individual data column, and models identity as user, role and agent together rather than agent alone.

What granularity can FaburAI enforce policy at?

Per user role, per AI actor, per MCP server, per tool, per table and per column. Deny overrides allow, so an explicit deny on a sensitive column cannot be widened by a broader allow rule elsewhere in the policy set.

How is FaburAI deployed?

One codebase, three deployment models: FaburAI-hosted SaaS, PaaS in the customer’s own cloud account, and fully on-premises on Kubernetes. In every model, governance runs in the customer’s own tenant and communication is outbound-only from their environment, so on-premises deployments do not require inbound firewall exceptions.

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Built for distributed enterprise AI governance

Govern AI. Everywhere.

The AI Mesh for AI-Native Enterprise

FaburAI helps enterprises see, understand, and govern AI across the distributed systems where it actually runs — without forcing everything into one platform or one gateway.

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Discover

Map the distributed AI surface across systems, teams, and execution paths.

Understand

See how AI, identities, tools, resources, and data are connected.

Control

Define, simulate, and enforce policy across the AI estate.

The problem

AI is spreading faster than enterprise control.

AI is being embedded into applications, workflows, agents, tools, and data paths across the enterprise. But most organizations still cannot clearly answer what is connected, what is allowed, what is exposed, or where policy is enforced.

FaburAI makes the distributed AI estate visible, governable, and controllable in place — without requiring every system, agent, or workflow to move into a single centralized platform.

Visibility is fragmented

AI activity spans platforms, tools, data, applications, teams, vendors, and business units.

Policy is disconnected

Governance often sits outside the execution paths where AI decisions and actions happen.

Catalogs are not enough

Enterprises need to understand governable relationships, identities, sensitive resources, and execution paths.

Neutrality matters

AI will remain distributed. Governance has to work across platforms, clouds, vendors, and infrastructure choices.

How it works

See what exists. Understand what is exposed. Govern what can happen.

FaburAI provides the governance foundation for an enterprise AI Mesh: a common way to understand and control AI across distributed execution surfaces.

Connect distributed AI surfaces
Point FaburAI at an MCP server and it reads what that server exposes — tools, resources and prompts — then introspects the data systems behind it down to the individual column. Nothing is hand-keyed, and nothing has to be centralized.
Catalog what is governable
Everything discovered lands in one canonical governance model: servers, tools, resources, prompts, tables, columns, roles and AI actors. Columns are scanned for sensitivity signals and tagged PII, PHI, GDPR, SOX or HIPAA.
Visualize the AI Graph
A five-column path view from user role through AI actor, MCP server, tool and table to column. Click a column to see every actor that has read it; click a role to see everything that role can reach.
Govern execution paths
Describe a policy in plain language, review the structure FaburAI drafts from it, and approve it. Only approved policies ever reach enforcement — an unapproved draft cannot govern traffic.

AI MeshAI GraphPolicy SimulationRuntime GovernanceExplainable EnforcementDistributed AI Control

The difference

Enforcement runs in your environment. Never in ours.

Governance products commonly enforce by sitting in the traffic between your agents and your tools. FaburAI works the other way around: we publish policy, and your own environment enforces it.

Out of the request path

Governed traffic never leaves your network to reach us, and your data never passes through our systems.

Not a single point of failure

Decisions are made locally. If FaburAI is unreachable, enforcement carries on — an outage on our side does not open your tools or stop your agents.

Column-level, not tool-level

Policy binds to user role, AI actor, tool, table and column. Deny overrides allow, so a broad grant cannot quietly widen access to a sensitive field.

How the platform works Compare approaches

The platform

Four surfaces, one governance model.

Connect, Catalog and Control are the governance lifecycle. Cockpit is the record of what actually happened.

AI Connect

Register and discover the AI surface: MCP servers, their tools and resources, the data systems behind them, and the AI actors calling in.

Explore AI Connect

AI Catalog

The canonical inventory — one governance model spanning servers, tools, columns, roles and agents, with sensitivity labels down to the column.

Explore AI Catalog

AI Control

Policy lifecycle and enforcement. Plain-language authoring, a human approval gate, and observe, simulate or enforce set per server.

Explore AI Control

AI Cockpit

Runtime observability. Every enforcement decision, with the full identity chain behind it — who, which agent, which tool, which column, which policy.

Explore AI Cockpit

Regulatory evidence

Governance that produces the evidence regulators ask for.

FaburAI does not certify you. It produces the artifacts a compliance program is built from: an inventory of AI systems, a decision record for every governed call, the identity chain behind each decision, and a human approval gate on every policy that enforces.

See your AI estate before you talk to anyone.

Take a self-service test drive of FaburAI, or talk to us directly if your team is thinking about AI governance, distributed control, runtime policy, or operational readiness for enterprise AI.