Is MuleSoft AI Gateway a security product?

It is an API governance layer extended to AI traffic. It carries real security-relevant policies, including PII detection, token rate limiting, regex prompt guarding, and delegated content safety through Bedrock Guardrails and Azure Content Safety. What it does not center is an identity-bound, signed per-decision audit record, and its identity handling authenticates the caller as a separate step rather than binding identity into the decision. It is strong governance and reuse; it is not built around producing independent regulatory evidence for each AI call.

Does MuleSoft AI Gateway produce an audit trail?

It produces Token Usage Reports, an API Manager LLM Summary with policy violations per hour, Message Logging, and OpenTelemetry traces. Anypoint's separate Audit Logging service records control-plane administrative actions, meaning configuration changes, rather than a per-request record of AI decisions. MuleSoft's documentation describes no cryptographic signing or tamper-evidence on gateway logs. Those artifacts are strong for operating a platform and for cost attribution. They are a different artifact than a signed, independent per-decision record built for regulatory review.

Can MuleSoft AI Gateway run air-gapped?

Not for the AI policies. LLM Proxy, LLM Token Based Rate Limit, and LLM PII Detection are unsupported in Local Mode, and Local Mode still registers with and reports usage to the MuleSoft control plane. A deployment that needs AI governance to run with no control-plane dependency has to design around that constraint. DeepInspect deploys self-hosted without that dependency.

Do MuleSoft AI Gateway and DeepInspect overlap?

They overlap on routing and basic PII policy, and they diverge on identity binding and audit evidence. The sensible pattern for a MuleSoft shop handling regulated data is to run both: the Omni Gateway as the control plane for all API and AI traffic, and DeepInspect at the AI request boundary for identity-bound policy and signed per-decision evidence. One governs breadth of traffic; the other produces depth of evidence for the AI calls specifically.

Which one fits a bank facing DORA and the EU AI Act?

If the bank already runs Anypoint, MuleSoft AI Gateway is a natural place to route and moderate AI traffic. The regulatory evidence requirement, a signed and independent per-decision record tied to identity, is where DeepInspect fits, because DORA review and EU AI Act Article 12 test the independence and integrity of the record. Most banks in this position run the platform they already own and add the evidence layer where the auditor's questions land.

DeepInspect vs MuleSoft AI Gateway: One Control Plane for Every API, and One Built for AI Evidence

MuleSoft AI Gateway reached general availability for its LLM capabilities on March 30, 2026. Salesforce markets it as "a single governed control plane for every AI interaction," and it governs three traffic types: LLM, MCP, and agent-to-agent (A2A). It runs on the Omni Gateway, which was renamed from Anypoint Flex Gateway and now ships as version 1.13. For a MuleSoft shop, the LLM governance capabilities cost nothing extra on Platinum, Titanium, Unlimited, and Integration Advanced tiers.

I want to be accurate about what it is, because a MuleSoft buyer will spot a lazy take immediately. This is API management extended to AI traffic, with real policies and deep reuse of an existing platform. The comparison with DeepInspect comes down to what the record of a decision is, and to whether the AI governance can run independent of the MuleSoft control plane.

TL;DR

MuleSoft AI Gateway routes and governs LLM, MCP, and A2A traffic through the Omni Gateway, with policies like LLM Token Based Rate Limit and LLM PII Detection, and it reuses your existing Anypoint identity and observability. Its records are token usage reports and OpenTelemetry traces. DeepInspect binds policy to the natural-person or agent identity, classifies prompt content across regulated data types, and commits a signed per-decision audit record on a write path the application never holds. In a MuleSoft estate that needs regulatory evidence, both can run.

MuleSoft AI Gateway: what it is and where it sits

The core construct is the LLM Proxy, one logical endpoint fronting multiple providers, with a limit of 50 LLM Proxies per Large Omni Gateway. It supports OpenAI and Azure OpenAI, Gemini, Bedrock for Claude, and NVIDIA Nemotron. Routing comes in two forms: Model-Based Routing, which is static, and Semantic Routing, which matches prompt content to a topic-defined route.

The AI policies are real and worth naming precisely:

LLM Token Based Rate Limit (first available in v1.11.0) does fixed-window token rate limiting, counting request, response, and reasoning tokens, and returns 429 with x-token-limit and x-token-remaining headers.
LLM PII Detection (v1.13.0) scans OpenAI-format bodies for Email, US SSN, Credit Card, and Phone Number, plus custom regex, with actions Reject, Log, or Log and mask, returning 403 on reject.
Regex Prompt Guard blocks requests matching deny-list patterns.
Amazon Bedrock Guardrails and Azure Content Safety delegate content moderation to those providers.

MCP and A2A each get their own policy families, including MCP Attribute-Based Access Control and the MCP Bridge that exposes existing APIs as agent-ready tools. This is a genuine control plane for agent and API traffic, and the reuse story is the whole value: one place for REST, SOAP, GraphQL, MCP, A2A, and LLM.

What DeepInspect is and where it sits

DeepInspect is a stateless proxy at the AI request boundary. It evaluates identity-bound policy per request, classifies prompt content against the regulated data types the organization recognizes, and commits a per-decision audit record with cryptographic integrity. Deterministic, fail-closed, model-agnostic in front of any HTTP LLM endpoint.

The primitives are narrower than MuleSoft's platform and pointed at evidence: natural-person or agent identity attribution taken from the application rather than inferred from a credential; per-route and per-role policy; prompt-level classification across PII, PHI, MNPI, source code, and jurisdictional categories; a pass, block, or modify decision before the request reaches the model; and a signed audit record shaped for EU AI Act Article 12, HIPAA, and DORA review.

Where the two separate

Both operate on HTTP AI traffic, so this is a comparison of the same layer, not of different stacks. Three differences carry the decision.

Identity. MuleSoft handles authentication through generic gateway policies: Client ID Enforcement, JWT Validation, OpenID Connect OAuth 2.0 token enforcement. Those authenticate the caller. The AI policies then run as a separate composed layer. The LLM Token Based Rate Limit policy can key on #[attributes.principal] to partition by user, which is real, but that is a rate-limit partition rather than an identity bound into a decision record. DeepInspect treats the natural person or agent as a first-class primitive that gets recorded against every decision.

The record. MuleSoft produces Token Usage Reports, an API Manager LLM Summary showing policy violations per hour, Message Logging, and OpenTelemetry tracing, with Fluent Bit shipping logs onward. Anypoint also has an Audit Logging service, and precision matters here: that service logs control-plane administrative actions, who changed which configuration, rather than a data-plane record of each AI decision. MuleSoft's documentation describes no cryptographic signing or tamper-evidence on any gateway log. DeepInspect commits a signed, tamper-evident record of each decision, on a write path the application cannot reach, which is the property that separates evidence from a log.

Independence. The AI policies require the MuleSoft control plane. LLM Proxy, LLM Token Based Rate Limit, and LLM PII Detection are all unsupported in Local Mode, and Local Mode itself still registers with and reports usage to the control plane. A deployment that needs its AI governance to run without a phone-home dependency has to account for that.

Feature comparison

| Capability | MuleSoft AI Gateway | DeepInspect | |---|---|---| | Governs LLM, MCP, A2A | Yes, one control plane | LLM and agent HTTP traffic | | Multi-provider routing | Yes, LLM Proxy, up to 50 per gateway | Forwards to a configured upstream | | Semantic routing | Yes | Out of scope | | Token rate limiting | Yes, LLM Token Based Rate Limit | Per-role and per-route | | PII detection in prompts | Email, SSN, Credit Card, Phone, custom regex | PII, PHI, MNPI, source code, jurisdictional | | Identity on the decision | Authenticated separately, keyed as a partition | Natural person or agent, bound to the record | | Signed, tamper-evident audit record | Not documented | Yes, committed before response | | Runs without vendor control plane | AI policies require the control plane | Self-hosted or managed | | Reuse across REST, SOAP, GraphQL | Yes, full API platform | AI traffic only |

Pick MuleSoft AI Gateway if...

You already run Anypoint Platform on a tier that includes it, and the AI governance costs you nothing extra while reusing identity, policy, and observability you already operate.
You want one control plane for REST, SOAP, GraphQL, MCP, A2A, and LLM rather than a separate AI-specific layer.
FinOps chargeback by business group and application is a primary driver, and Token Usage Reports answer it directly.
Semantic routing and multi-provider failover without touching application code matter to you.

Pick DeepInspect if...

You need a signed, identity-bound, per-decision audit record that an EU AI Act Article 12, HIPAA, or DORA reviewer accepts as independent evidence.
You need prompt classification across PHI, MNPI, and jurisdictional categories, not only the four PII types the LLM PII Detection policy ships with.
You need AI governance that runs self-hosted without a dependency on a vendor control plane.
Identity has to be bound into the decision and the record, not composed as a separate authentication step.

Pricing approach

MuleSoft AI Gateway's LLM capabilities are included at no additional cost for Anypoint customers on Platinum, Titanium, Unlimited, and Integration Advanced tiers, so the cost is the underlying Anypoint license. DeepInspect is priced through a sales conversation and deploys self-hosted or managed. Neither publishes per-token pricing for the governance layer itself.

DeepInspect

This is the gap DeepInspect closes in a MuleSoft estate. MuleSoft governs the traffic across your whole API surface. DeepInspect produces the evidence record for the AI decisions inside it.

Run the Omni Gateway where it is strong, as the control plane for every API including the routing and moderation of AI traffic. Run DeepInspect at the AI request boundary where regulatory evidence is the requirement, binding each call to a verified identity, classifying the prompt across the regulated categories your sector recognizes, and committing a signed record before the model responds. The two compose in the same data path, one governing traffic broadly and one producing decision evidence narrowly. If you run MuleSoft and you are facing the August EU AI Act deadline, book an audit at deepinspect.ai.