Salesforce first sought to tackle AI agent sprawl last year with Agent Fabric, a suite of capabilities and tools inside its MuleSoft AnyPoint Platform. Now, it’s seeking to further rein in unruly AI agents on its platform and those of other vendors too, with new governance tools and deterministic controls.

When enterprises adopt multiple agentic AI products, they can end up redundant or siloed workflows or scattered across teams and platforms, undermining operational efficiency and complicating governance as they try to scale AI safely and responsibly.

Agent Fabric, introduced in September 2025, started out as a place for enterprises to register, view, interconnect and govern agents. In January it added a deterministic scripting tool and the ability to scan for new agents and add them to the registry.

But enterprises still need more help to bring their AI agents under control, so Salesforce is adding more features.

First up is an expansion of the deterministic controls in the form of Agent Script for Agent Broker, an intelligent routing service inside Agent Fabric that is designed to connect agents across domains, dynamically matching user tasks with the best-fit agent. Salesforce said the controls will help developers codify workflows in multi-agent systems in order to ensure consistent and reliable outputs.

Rather than leave probabilistic agents to make all the decisions about how to resolve a problem, introducing an element of unpredictability, Agent Script for Agent Broker enables enterprises to steer some of the decision-making according to predetermined rules that require fewer computing resources than running a large language model.

That’s welcome news for Robert Kramer, managing parter at KramerERP.

“Pure autonomous agents don’t necessarily work in production as enterprises need to ensure predictable outcomes. The deterministic controls should facilitate a secure handoff of control and rules while still allowing the model to engage in reasoning when it’s appropriate,” he said. “It’s a balance between control and flexibility, which is the norm for most real deployments.”

For Rebecca Wettemann, principal analyst at Valoir, providing both deterministic and probabilistic options within Agent Fabric enables developers and agent builders to take the lower-cost route to more accurate and predictable results from agentic systems.

Enterprises will have to wait to put this deterministic orchestration feature into production, though: Still in beta testing, it won’t be generally available until June 2026.

Centralized LLM governance tackles cost

Beyond orchestration, Salesforce has added a new LLM Governance capability in AI Gateway, the control layer within Agent Fabric that provides centralized visibility of token usage, costs, and data flows for third-party model.

Enterprises will be able to use LLM Governance, now generally available, to help them keep their AI operations on budget, Salesforce said.

This is becoming increasingly important as CIOs seek to bring disparate AI systems under centralized control and justify spiralling AI costs.

Info-Tech Research Group advisory fellow Scott Bickley warned that without centralized governance like this, different teams around a company may choose different models, negotiate their own API contracts, and manage token budgets locally.

“This results in sprawling costs, inconsistent security postures, and no enterprise-wide policy enforcement,” he said. “By positioning AI Gateway as the choke point through which all LLM traffic flows, enterprises gain visibility into AI usage patterns, the models in use, purpose of the usage, and cost data.”

MCP additions simplify integration

Salesforce is also adding new Model Control Protocol features, including MCP Bridge to make it easier to access legacy APIs, and Informatica-hosted MCPs, that it says will simplify how agents interact with enterprise data and APIs.

These could save developers time and simplify the building of cross-environment, multi-agent systems.

Bickley said MCP Bridge will help enterprises with thousands of legacy APIs (REST, SOAP, GraphQL) built long before MCP existed.

“Agents speaking MCP cannot call those APIs natively so they require wrappers around the API endpoint; this would be a massive engineering lift. MCP Bridge allows these APIs to be exposed as MCP-compatible tools without modifying the underlying code,” he said.

And Wettemann said Informatica-hosted MCPs will further reduce development overhead by bringing built-in data quality and governance capabilities into agent workflow, particularly critical for enterprises in regulated industries and those with heightened risk concerns.

But Bickley added a note of caution. “APIs can behave oddly and have their own nuanced behavior,” he said. “Enterprises should test how MCP Bridge handles edge cases.”

Informatica-hosted MCPs will not be a miracle solution either, he warned: “Even if the Informatica data quality and governance capabilities are cleanly integrated in the Agent Fabric registry, these are not instantaneous operations. Checking data fields for accuracy, deduplication, and cross-system matching take time and carry latency measured in milliseconds or even multiple seconds, and that is pre-integration.”

A pivot for MuleSoft?

Bickley sees the updates as a broader strategy for Salesforce to reposition MuleSoft, which it acquired in 2018 for $5.7 billion, from a traditional API integration platform to an infrastructure layer for enterprise AI agents.

By layering orchestration, governance, and connectivity into Agent Fabric, Salesforce appears to be trying to position MuleSoft as the system of record for how agents are discovered, routed, and governed across the enterprise, deepening its role beyond API management into core AI infrastructure, he said.

Not all CIOs will welcome that move.

“If your agent control plane runs on Agent Fabric, switching costs rise materially, and the more agents you register, the more orchestration rules and governance policies defined, the more difficult it becomes to move to an alternative solution,” the analyst said.

As with any critical infrastructure dependency, “CIOs need to ask:  What is the exit path?  What components of Agent Fabric are portable and what is locked in?  What’s the pricing model?  What is the integration depth with non-Salesforce agents and data sources?” he said.

For now, though, enterprises have plenty of AI agent orchestration options to choose from.