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An integrated runtime substrate that hosts, orchestrates, and governs multiple AI agents alongside the models, tools, and data they depend on.
An agent fabric provides the underlying platform layer for agentic AI deployments - combining agent runtime, tool access, identity and authentication, policy enforcement, and observability into a single managed environment. Where service-oriented architectures relied on application servers and APIs, agentic architectures rely on the fabric to handle the harder coordination problems: which agents are allowed to call which tools, how their actions are audited, where their inputs and outputs are logged, and which controls trigger before an action executes. The fabric is becoming the natural runtime integration point for AI governance controls, distinct from the inventory and intake work that happens before deployment.
Real world example:
A multinational bank deploying agents across customer service, fraud investigation, and compliance review settles on a single agent fabric to standardize identity, action-logging, and tool-access policies. When new agents come online, they inherit the fabric's controls automatically rather than each team building its own observability stack.
