Quick Summary:

MuleSoft Agent Fabric is Salesforce's answer to one of the biggest emerging challenges in enterprise AI: agent sprawl. As organizations deploy dozens of AI agents across teams, platforms, and vendors, those agents risk becoming disconnected, redundant, and ungovernable. Agent Fabric solves this with four core capabilities: Agent Registry, Agent Broker, Agent Governance, and Agent Visualizer, which together act as a centralized control layer for every AI agent in your enterprise. Generally available since October 2025 and built into the Anypoint Platform, it extends MuleSoft's proven integration heritage into the age of agentic AI. For businesses already investing in Salesforce Integration services or MuleSoft integration services, Agent Fabric is the natural next step.

Let's be honest about where enterprise AI actually stands right now.

It is not that companies are not adopting AI agents; they absolutely are, and fast. According to Salesforce's own data, AI agent adoption is projected to surge by 327% over the next two years, with 40% of enterprise applications expected to include embedded agents within a year. By 2029, the number of actively deployed AI agents worldwide could exceed one billion.

The problem is what happens after you deploy them. One team builds a customer service agent in Salesforce Agentforce. Another spins up a pricing agent on Amazon Bedrock. The IT department has a compliance agent running on a custom LLM. The HR platform came bundled with its own AI assistant. And suddenly, without anyone planning for it, you have dozens of agents operating in isolation, no shared visibility, no coordination, no governance. Different vendors, different protocols, different security models, zero interoperability.

This is what the industry now calls agent sprawl, and it is rapidly becoming the defining integration challenge of the AI era.

MuleSoft Agent Fabric was built to solve exactly this problem. Announced at Dreamforce 2025 and generally available since October 2025, it is the connective tissue that turns a fragmented collection of AI agents into a coordinated, trusted, governed network. Think of it as what API management did for applications, now applied to intelligence itself.

This blog breaks down how Agent Fabric works, what makes it different, and why it matters for enterprises that are serious about scaling AI responsibly.

What is MuleSoft Agent Fabric?

Featured Snippet: MuleSoft Agent Fabric is a platform solution from Salesforce that enables enterprises to discover, orchestrate, govern, and observe any AI agent — regardless of where it was built or which platform it runs on. It provides a single, centralized control layer for managing the full lifecycle of AI agents across an enterprise ecosystem, built on top of MuleSoft's Anypoint Platform.

The clearest analogy Salesforce uses is that of an air traffic controller. Just as an air traffic controller manages planes from dozens of different airlines, ensuring they take off, land, and share airspace without colliding, MuleSoft Agent Fabric manages AI agents from dozens of different vendors and platforms, ensuring they operate coherently, securely, and without conflict.

What makes this positioning significant is the word 'any.' Agent Fabric does not just govern Agentforce agents. It governs agents built on Amazon Bedrock, Google Vertex AI, Microsoft Copilot Studio, and custom in-house LLMs. It supports both MCP (Model Context Protocol) and A2A (Agent2Agent) communication standards, making it genuinely vendor-neutral.

This matters because, as Andrew Comstock, SVP and GM of MuleSoft at Salesforce, put it, the strategic challenge today is not building a single agent; it is enabling all of them to work together. Agent Fabric gives organizations the infrastructure to do that.

It is worth noting how naturally this extends MuleSoft's existing role in the enterprise. For years, MuleSoft integration services have helped businesses connect applications, data, and people through APIs. Agent Fabric applies that same connectivity philosophy to AI, treating agents as first-class enterprise assets that need to be cataloged, connected, secured, and monitored, just like any other critical system.

The Problem It Solves: Agent Sprawl Explained

To understand why Agent Fabric matters, you first need to understand what agent sprawl actually looks like in practice and why it is worse than it sounds.

Agent sprawl is what happens when multiple AI agents are deployed across an organization without a unified framework to manage them. Each team adopts what works for their use case. Marketing builds a campaign assistant. Finance deploys a forecasting agent. IT creates a support triage bot. Procurement gets an AI-powered vendor matching tool bundled with their SaaS. None of these were bad decisions individually.

But collectively? They create a mess. According to industry research cited by MuleSoft, 79% of organizations already report some level of agentic AI adoption in 2025, with 96% planning to expand. Yet the governance frameworks to support that expansion are lagging far behind.

The consequences of unmanaged agent sprawl are concrete and serious:

• Duplicated development: teams rebuild agents that already exist elsewhere in the org
• Compliance blind spots: agents accessing sensitive data without consistent policy enforcement
• Security vulnerabilities: agents making external calls or storing data without proper authentication controls
• Inconsistent outputs: agents performing similar tasks but producing contradictory results
• Zero interoperability: agents cannot collaborate across domains because they speak different protocols

As HyperFRAME Research analyst Stephanie Walter has noted, agent sprawl is highly likely to threaten operational efficiency and complicate governance, making it harder for enterprises to scale AI responsibly. Robert Kramer of Moor Insights and Strategy adds a useful frame: just as APIs required gateways and management, agents now need coordination, governance, and observability.

MuleSoft Agent Fabric is that coordination layer.

The Four Core Pillars of MuleSoft Agent Fabric

Agent Fabric is organized around four capabilities that work together to bring order to an enterprise's agent ecosystem. Each one addresses a different dimension of the agent management challenge:

1. Discover: Agent Registry

The first challenge in managing agents is knowing they exist. Agent Registry solves this by providing a central catalog built on Anypoint Exchange where every AI agent, MCP server, LLM, and automation tool across the enterprise can be registered and made discoverable.

This is not just a passive inventory list. Developers can search for existing agents using natural language queries through Vibes inside Anypoint Code Builder. Other agents can dynamically query the registry to find the right tool for a task at runtime. And IT teams get real-time awareness of every active agent across the ecosystem.

Agent Scanners take this further by automatically detecting and cataloging agents running across Amazon Bedrock, Google Vertex AI, Microsoft Copilot Studio, and Salesforce Agentforce without requiring manual registration. The moment an agent is deployed anywhere in your connected ecosystem, it appears in the registry.

The practical outcome is straightforward: teams stop rebuilding what already exists, and governance starts from a foundation of visibility.

2. Orchestrate: Agent Broker

Discovery is only useful if agents can actually work together. The Agent Broker is the AI Agent Orchestration engine at the heart of Agent Fabric, an intelligent routing service that organizes agents into business-focused domains and dynamically routes tasks to the right agent at the right time.

The Broker is powered by the LLM of your choice, making it flexible rather than locked into Salesforce's own models. It communicates with agents using both MCP (for agent-to-system communication) and A2A (for agent-to-agent communication), enabling multi-step workflows where multiple specialized agents collaborate in sequence.

A real-world example makes this concrete. Consider a mortgage application process. A customer inquiry comes in through a Mortgage Assistant agent built on Agentforce. The Agent Broker routes that inquiry across: a Credit Check Agent for real-time credit verification, a DocuSign IAM Agent for secure document signatures, a Compliance Agent built in-house to enforce regulatory requirements, and a Fraud Detection Agent running on a third-party platform. The customer experiences a seamless interaction. Behind the scenes, four specialized agents collaborated across entirely different platforms all governed, all traceable, all secure.

This is the promise of AI Agent Orchestration done right: not a single monolithic agent trying to do everything, but specialized agents collaborating intelligently.

3. Govern: Agent Governance

Governance is arguably the most critical pillar and the one that most enterprises skip until something goes wrong. Agent Governance extends MuleSoft's Anypoint Flex Gateway to support MCP and A2A protocols, applying enterprise-grade security and compliance controls to every single agent interaction.

This means every client, whether human, application, or another AI agent, must be authenticated before interacting with any governed agent. Security policies, rate limits, data access controls, and compliance rules are enforced centrally, not scattered across individual agent configurations.

A particularly important concept here is Trusted Agent Identity. As tasks pass from one agent to another through multi-step workflows, Agent Governance propagates verified user identity claims across those boundaries using OAuth2 and OIDC standards. This matters enormously for regulated industries: when a compliance agent makes a decision based on data retrieved by three other agents, you need a tamper-proof record of who authorized what at every step.

For enterprises operating under GDPR, CCPA, HIPAA, or sector-specific financial regulations, this is not optional infrastructure; it is table stakes.

4. Observe: Agent Visualizer

You cannot govern what you cannot see. Agent Visualizer provides a dynamic, interactive map of the entire agent ecosystem showing how agents, systems, LLMs, and humans interconnect, where tasks are routed, and how performance looks across the network in real time.

This is fundamentally different from traditional API monitoring. Standard API metrics tell you whether a request succeeded or failed. Agent Visualizer traces the decision paths of AI agents, showing which agent received a task, which tools it consulted, where it escalated to a human, and where latency or anomalies appeared in the chain. Integrated with Anypoint Monitoring, it provides the logs, traces, and performance metrics that turn a black box into an auditable system.

For enterprise teams trying to demonstrate ROI on AI investment, having clear visibility into how agents behave and being able to optimize based on that data is exactly what converts pilot projects into production-scale programs.

Real-World Use Cases of Mulesoft Agent Fabric

Agent Fabric is not a theoretical platform. Organizations across industries are already building on it.

Banking and Financial Services: Mortgage Processing

A bank's Agentforce Mortgage Assistant handles incoming customer inquiries and uses the Agent Broker to coordinate across a credit check agent, a document verification agent (via DocuSign), a regulatory compliance agent, and a fraud detection agent all running on different platforms, all governed under a single security model. Loan processing time that once required multiple departments and days of handoffs now completes in a single governed, multi-agent workflow. Human approvers are looped in only at the high-stakes decision points where their judgment is genuinely required.

Retail: Inventory and Pricing Intelligence

A global retailer runs separate agents for inventory tracking, dynamic pricing, fraud detection, and customer communication. Without Agent Fabric, each of these operates independently. With it, a low-stock alert from the inventory agent automatically triggers the pricing agent to adjust, the fraud agent to validate the reorder anomaly, and the customer service agent to send proactive notifications to affected customers. The entire chain executes within seconds, across three different platforms, with full governance and traceability.

Healthcare: Multi-System Patient and Operations Coordination

Healthcare organizations like Rush University System for Health are deploying Agent Fabric to coordinate agents across patient scheduling, clinical documentation, compliance, and supply chain operations. In an industry where data privacy regulations are strict and human oversight is non-negotiable, Agent Fabric's governance layer and human-in-the-loop escalation capabilities are exactly what make responsible AI deployment possible.

Enterprise Operations: Scaling Across Divisions

For large enterprises managing AI across dozens of business units, think global logistics, HR, commercial operations, and R&D, all running different agents. Agent Fabric provides the unified visibility and governance layer that makes enterprise-wide AI adoption tractable rather than chaotic. Barco and Wynn Encore Las Vegas are among the early adopters using Agent Fabric to manage agents at that scale.

Recommended Read: A Comprehensive Guide To Salesforce Cloud Types

MuleSoft Agent Fabric vs. Traditional API Management

A question that comes up often in Salesforce Integration services conversations is: how is this different from what MuleSoft already does? The table below makes the distinction clear.

The key insight from this comparison is that Agent Fabric does not replace traditional API management; it extends it. Your existing MuleSoft integration services investments remain fully relevant. Agent Fabric adds a new layer of intelligence and governance on top of the integration foundation you already have.

Final Words

Enterprise AI is no longer in the experimental phase. It is becoming operational infrastructure, and that means the management challenges that come with any complex infrastructure are now fully in play.

The question for enterprise leaders today is not whether to deploy AI agents. Most already have. The question is whether those agents are working together, governed properly, visible to the teams responsible for them, and capable of scaling without creating more problems than they solve.

MuleSoft Agent Fabric answers that question with a platform built on two decades of MuleSoft's integration expertise, now extended into the age of AI. It treats agents the way mature enterprises already treat APIs and applications as assets that need to be discovered, connected, secured, and monitored. The result is what Salesforce calls the Agentic Enterprise: a model where humans and AI work side by side, with the clarity and control needed to do so responsibly.

For companies already on the Salesforce ecosystem or investing in MuleSoft integration services to connect their technology stack, Agent Fabric is the natural evolution of the integration layer they have already built.

At DianApps, we help enterprises design, implement, and optimize their Salesforce and MuleSoft architecture, including Agent Fabric implementations that get AI agents working together from day one, not after sprawl has already set in. Whether you are starting your agentic journey or trying to bring order to an existing agent ecosystem, our certified team can help you build it right.