NeuralTrust vs TrueFoundry: Best for Enterprise AI Security?

This comparison is written for enterprise security and platform leaders (CISOs, CIOs, Heads of AI, and platform engineering teams) evaluating an AI gateway as the control layer for LLM, MCP (Model Context Protocol), and agent traffic. It compares two products in that category: NeuralTrust TrustGate and the TrueFoundry AI Gateway.

An AI gateway sits between AI agents and the services they call (LLM providers, MCP tool servers, and other agents) and becomes the single place where routing, policy, security enforcement, and observability attach. Both TrustGate and TrueFoundry operate at this layer, cover LLM and MCP traffic, and can be deployed inside a customer's own infrastructure.

The two products differ in scope and origin. TrustGate is built by a security company and treats runtime security enforcement as the gateway's organizing principle. TrueFoundry is a broader Kubernetes-native enterprise AI platform: its AI Gateway is one component of a control plane that also covers model deployment, self-hosted model serving, an MCP gateway, an agent gateway, and prompt management, and it recently expanded its footprint by acquiring the open-source MLOps platform Seldon AI (June 24, 2026). This article compares the gateway component of each vendor on architecture, runtime security, posture management, governance, MCP and tool controls, observability, and deployment.

Related article: The 11 Best AI Gateways for Enterprise AI Security in 2026

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Executive Summary (TL;DR)

• TrustGate is security-first, positioning as "the AI gateway built by a security company." Its differentiating design choice is a Security Engine that attaches to every Route, into which NeuralTrust's own runtime security product (TrustGuard) plugs.
• TrustGate ships a first-party runtime detection engine. TrueFoundry's guardrails include built-in PII and toxicity handling but also lean on integrations with external services (OpenAI Moderation, AWS Guardrails, Azure Content Safety/PII) rather than a first-party multi-turn behavioral detection engine.
• NeuralTrust offers a companion posture product (TrustLens) that discovers and assesses AI running outside the gateway's path, a distinct posture layer TrueFoundry does not position as a separate product.
• TrustGate emphasizes a single unified multi-protocol trace tree across LLM, MCP, and A2A traffic, with cost, latency, and security findings attributed inline.
• TrueFoundry is a strong, enterprise-proven platform with very broad model coverage (the platform cites 1,000+ to 1,600+ models), Kubernetes-native deployment, and a genuinely strong data-sovereignty story: VPC, on-prem, and air-gapped, with tenant isolation physically backed by Kubernetes namespaces.
• TrueFoundry is broader than a gateway. It also serves self-hosted models (vLLM, SGLang, Triton, KServe), offers an MCP gateway with tool-level RBAC and OAuth 2.0, an agent gateway, and prompt management, and integrates the Seldon Core open-source MLOps foundation after its June 2026 acquisition.
• TrueFoundry's governance features are largely standard rather than feature-gated, but the platform assumes and rewards a Kubernetes operating model, which is an adoption consideration for teams not already on Kubernetes.
• Both keep data inside the customer's infrastructure and both reserve their deepest value in an enterprise deployment.

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Comparison at a Glance

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Platform Overview

What is NeuralTrust TrustGate?

TrustGate is NeuralTrust's AI gateway. It sits between agents and the services they call (LLM providers, MCP servers, and other agents) and is designed to be the one place where routing, policy, security, and observability attach across all three kinds of AI traffic. Its core abstractions are Consumers, Providers, Routes, and Policies. Provider connections are configured once and reused; routing, failover, retries, and caching live in the gateway rather than in each application's code.

TrustGate's defining design choice is that a Security Engine attaches to every Route: when one is attached, every request is inspected and an allow/block/transform decision is executed before the request reaches its target. Security findings render as first-class spans in the same trace tree as operational telemetry. NeuralTrust positions this as the architectural consequence of being "the only AI gateway built by a security company."

Per NeuralTrust's own documentation, TrustGate is explicitly not itself the content-detection product (that is TrustGuard, the engine that attaches) and not a posture-management product (that is TrustLens, a separate product). The gateway core is Apache 2.0 and open source; the governance layer, retention, and security-finding depth are commercial.

What is TrueFoundry AI Gateway?

TrueFoundry AI Gateway is one component of TrueFoundry's broader enterprise AI platform. As a gateway, it provides a unified, OpenAI-compatible API to a very large catalog of models (the platform cites 1,000+ to 1,600+ models across providers), covering chat, completion, embedding, and reranking. It adds routing and fallbacks (latency-based, weighted, geo-aware), rate limiting and token/cost quotas, RBAC with SSO, full request/response logging, and OpenTelemetry-based observability.

What makes TrueFoundry distinctive is scope and deployment model. It is Kubernetes-native and designed to run fully inside the customer's environment (SaaS, hybrid, or self-hosted in VPC, on-prem, or air-gapped), with tenant isolation physically backed by Kubernetes namespaces. Beyond the gateway, the platform serves self-hosted open-source models (vLLM, SGLang, Triton, KServe), offers an MCP gateway (with a registry, tool-level RBAC, OAuth 2.0, and federated identity), an agent gateway, and prompt management. In June 2026, TrueFoundry acquired Seldon AI, whose open-source Seldon Core adds a mature real-time ML serving foundation to the platform. TrueFoundry can be used as a standalone gateway or as part of the full platform.

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Architecture Comparison

Both are software gateways deployed inside the customer's infrastructure, and both use a control-plane / data-plane model.

TrustGate organizes around Consumers, Providers, Routes, and Policies, and is designed so that a Security Engine attaches at the Route level as a foundational concern. It covers LLM, MCP, and A2A traffic in one model and renders security findings inline in the trace tree. NeuralTrust's stated deployment model is an open-source self-hosted core, with managed and hybrid (VPC, air-gapped) deployment at the enterprise tier. It is a purpose-built AI gateway rather than a broader MLOps platform.

TrueFoundry is Kubernetes-native by design. Its gateway runs the hot path (auth, rate limits, guardrails, traces) inside the customer's Kubernetes cluster, with a control plane that also manages model deployment and serving. Tenant isolation is physically backed by Kubernetes namespace boundaries rather than being purely logical, which is a genuine architectural strength for multi-team enterprises. The platform is cloud-agnostic and positions itself as a hyperscaler alternative. The trade-off is that TrueFoundry's architecture assumes a Kubernetes operating model; teams that do not run Kubernetes (or do not want to) take on that model to adopt it, and the platform's breadth is more than a team that only needs a thin gateway may want.

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Runtime AI Security

This is the central difference, and it is a difference of model.

TrustGate places a Security Engine attachment at the center of its design: NeuralTrust's own runtime product, TrustGuard, plugs in and inspects every request inline, with the decision executed before the request reaches its target. NeuralTrust positions TrustGuard as delivering conversation-level and multi-turn analysis rather than isolated per-request filtering. Two honest caveats: the content-detection capability is TrustGuard (a separate, attachable product), not the bare gateway, and TrustGuard's specific detections should be verified against its own documentation.

TrueFoundry provides configurable guardrails on both input and output paths: it can scan for PII, prompt injection patterns, and disallowed topics before a request reaches a model, and evaluate responses for toxicity, bias, and policy violations. It documents built-in PII/PHI and secrets detection that requires no external service, plus custom rules written as configuration or Python, and it can plug into external services such as OpenAI Moderation, AWS Guardrails, and Azure Content Safety. This is a capable, defense-in-depth guardrails framework. The distinction for a security buyer: TrueFoundry's guardrails are a configurable framework that combines built-in checks with external integrations and custom code, rather than a single first-party detection product engineered as the platform's reason for existing, and multi-turn behavioral analysis is not positioned as a core, dedicated capability the way TrustGuard is.

Bottom line: TrustGate offers a first-party engine from a security company, attached inline as the gateway's organizing principle, with multi-turn analysis positioned as core. TrueFoundry offers a strong, flexible guardrails framework (built-in plus integrations plus custom code) inside a broader platform. Which fits depends on whether the buyer wants a dedicated security-company detection stack or a capable guardrails layer within an enterprise AI platform.

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AI Security Posture Management (AI-SPM)

Posture management means discovering and assessing AI agents, tools, and models across the estate, including those that do not route through the gateway.

Neither gateway does this on its own. For TrustGate, NeuralTrust's documentation is explicit that discovering and assessing AI outside the gateway's path is the job of TrustLens, a separate NeuralTrust product that consumes gateway signals. For TrueFoundry, governance and visibility are centered on the traffic and workloads that run through the platform; estate-wide discovery of ungoverned AI outside the platform is not positioned as a distinct posture product.

On a strict gateway-only basis this is a tie: neither gateway is a posture-management product. The difference is the shape of the answer. NeuralTrust offers a dedicated companion posture product (TrustLens) aimed at the full AI estate, including AI that never touches the gateway. TrueFoundry's strength is deep control over what runs on its platform (which, given its model-serving scope, can be a large share of an enterprise's AI), rather than a separate discovery layer for AI running entirely outside it.

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AI Governance

TrueFoundry's governance is a genuine strength, particularly its physical multi-tenancy: tenant isolation backed by Kubernetes namespaces, two-layer RBAC, workspace-scoped deployments, and per-project rate limits that scale from a few teams to hundreds without proportional configuration growth. Third-party analysis notes that TrueFoundry tends to include governance features as standard rather than gating them behind higher pricing tiers. TrustGate similarly provides Consumer-based access and reserves SSO/SAML, RBAC, and long-term retention for its enterprise tier. For a security review, both deliver enterprise governance; TrueFoundry's differentiator is namespace-level isolation, while TrustGate's is security findings as first-class spans in the trace.

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MCP & Tool Governance

Both products have a strong MCP governance story, and TrueFoundry's is broad.

TrustGate governs MCP traffic that flows through it: per-Consumer tool access, tracing of every tool invocation (which tool, which arguments, which Consumer, which result, at what cost), and a unified audit trail. NeuralTrust's documentation is explicit that TrustGate is not an MCP connectivity platform and does not ship a library of pre-built MCP integrations; it governs the servers the customer registers.

TrueFoundry offers a dedicated MCP Gateway with a central registry: register internal or third-party MCP servers, discover them through a unified endpoint, and apply per-server and tool-level RBAC, OAuth 2.0, and federated identity (Okta, Azure AD) to every tool call. Access control is enforced at the visibility level (an agent only discovers tools it is authorized to use, which limits the blast radius of prompt injection), with a single gateway key exchanged for per-server tokens behind the scenes, plus observability, approval flows, rate limits, and caching. It ships prebuilt MCP servers for common enterprise tools (Slack, GitHub, Confluence, Datadog) and lets teams register custom servers via an SDK or any backend. This is one of TrueFoundry's strongest areas.

Neither product's core value is a giant catalog of third-party MCP integrations, though TrueFoundry does provide prebuilt connectors for common tools plus registry-based governance. If a large managed MCP catalog is a hard requirement, qualify it for both.

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Observability

Both provide strong observability.

TrustGate resolves a full agent workflow into a single trace tree (the model call, the MCP tool calls it triggers, and A2A delegations) with cost, latency, and security findings attributed at every level (Consumer, Route, Provider, span). NeuralTrust frames this unified multi-protocol trace as a differentiator, with security findings inline in the same view. Live observability is in the open-source core; long-term retention and historical analytics are commercial.

TrueFoundry provides OpenTelemetry-compliant metrics, traces, and full request/response logging, with token usage, latency (P99/P90/P50, time-to-first-token, inter-token latency), error rates, and cost broken down by model, team, user, environment, or custom metadata. It offers request-level inspection and agent/MCP traces, and exports to external backends (Grafana, Datadog, Prometheus), running the telemetry path inside the customer's cluster. This is mature, enterprise-grade observability that integrates cleanly into existing stacks.

The practical difference is emphasis: TrustGate centers a unified multi-protocol trace with security findings inline in the same view; TrueFoundry offers deep, OpenTelemetry-native observability across the platform, exportable to the tools an enterprise already runs.

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Deployment

Deployment and data sovereignty are TrueFoundry's strongest dimension: fully self-hosted, cloud-agnostic, Kubernetes-native, with the entire hot path (auth, guardrails, traces) and data staying inside the customer's cluster, and physical tenant isolation via namespaces. TrustGate positions air-gapped and hybrid at its enterprise tier and also keeps data inside the customer's perimeter. Both are strong for data-residency-sensitive buyers; TrueFoundry's edge is depth of Kubernetes-native isolation, at the cost of assuming a Kubernetes operating model.

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Detailed Feature Comparison

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Which Platform Should You Choose?

Choose NeuralTrust TrustGate if...

• Your driver is a security mandate and you want the runtime-security engine to be a first-party product from a security company, engineered as the gateway's reason for existing rather than one configurable layer inside a broad platform.
• You want multi-turn and conversation-level analysis positioned as core, and you will validate TrustGuard's detections against its documentation.
• You want security findings inline in the same trace tree the platform team already reads.
• You expect to also adopt a companion posture product (TrustLens) to cover AI outside the gateway's path.
• You want a focused AI gateway rather than a full Kubernetes-native MLOps and deployment platform.
• You do not run Kubernetes, or prefer not to adopt a Kubernetes-centric operating model to get a gateway.

Choose TrueFoundry if...

• You are a Kubernetes-native enterprise and want one control plane for the AI gateway, self-hosted model serving, MCP, agents, and (post-Seldon) traditional ML.
• Data sovereignty is paramount and you require fully self-hosted, cloud-agnostic deployment (VPC, on-prem, air-gapped) with physical, namespace-level tenant isolation.
• You want to serve your own open-source models (vLLM, SGLang, Triton, KServe) behind the same gateway that routes hosted models.
• You need strong MCP governance with a registry, tool-level RBAC, OAuth 2.0, federated identity, and prebuilt enterprise connectors.
• You value governance features included as standard rather than gated behind higher tiers, and you have the Kubernetes expertise to operate the platform.
• You want to consolidate multiple AI infrastructure tools into a single platform to reduce operational silos.

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Final Verdict

Both are credible, enterprise-capable choices, and both keep data inside the customer's infrastructure. TrueFoundry's advantages are breadth and deployment depth: a Kubernetes-native platform that unifies the gateway with self-hosted model serving, MCP and agent governance, and (after the Seldon acquisition) traditional ML, with best-in-class data sovereignty and physical tenant isolation. TrustGate's advantages are a first-party inline security engine, multi-turn analysis positioned as core, unified multi-protocol tracing with security findings in the same view, and a dedicated companion posture product.

The decision usually turns on two axes. The first is the security model: TrustGate treats a first-party Security Engine attachment as the gateway's reason for existing and delivers detection from a single security company, while TrueFoundry provides a strong, configurable guardrails framework (built-in checks plus external integrations plus custom code) within a broader platform. The second is scope and operating model: TrueFoundry is the natural choice for Kubernetes-native enterprises that want to consolidate models, agents, and tools on one control plane, whereas TrustGate is a focused, security-first AI gateway that does not require adopting a full platform or a Kubernetes-centric model.

A security-led buyer who wants a first-party enforcement substrate with multi-turn analysis and a dedicated posture companion will likely prefer TrustGate. A Kubernetes-native enterprise that wants one sovereign control plane spanning gateway, model serving, MCP, and agents will likely prefer TrueFoundry.

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Key Takeaways

• TrustGate's biggest differentiators are a first-party Security Engine (TrustGuard) with multi-turn analysis, unified multi-protocol tracing with inline security findings, and a companion posture product (TrustLens).
• TrueFoundry is a broad, Kubernetes-native enterprise AI platform: the AI gateway is one part of a control plane spanning model serving, MCP, agents, prompt management, and (post-Seldon) MLOps.
• TrueFoundry's standout strengths are data sovereignty (VPC, on-prem, air-gapped, cloud-agnostic) and physical tenant isolation via Kubernetes namespaces.
• TrueFoundry's runtime security combines built-in PII/toxicity detection with external integrations (OpenAI Moderation, AWS Guardrails, Azure Content Safety) and custom rules, rather than a dedicated first-party multi-turn detection engine.
• TrueFoundry has a strong MCP gateway: registry, tool-level RBAC, OAuth 2.0, federated identity, and prebuilt enterprise connectors.
• TrueFoundry acquired Seldon AI (June 24, 2026), adding the open-source Seldon Core MLOps foundation to its platform.
• TrueFoundry assumes and rewards a Kubernetes operating model, which is an adoption consideration for teams not already on Kubernetes.
• The choice usually reduces to a first-party security-company gateway (TrustGate) versus a broad, sovereign, Kubernetes-native AI platform (TrueFoundry).

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Frequently Asked Questions

1. What is the difference between NeuralTrust TrustGate and TrueFoundry?

TrustGate is a security-first, purpose-built AI gateway whose Security Engine (TrustGuard) attaches to every Route, with a companion posture product (TrustLens). TrueFoundry is a broader Kubernetes-native enterprise AI platform whose AI Gateway is one component alongside model serving, an MCP gateway, an agent gateway, and prompt management, with security delivered as a configurable guardrails framework.

2. Does TrustGate support on-prem or air-gapped deployment?

NeuralTrust positions managed and hybrid deployment, including VPC and air-gapped, at its enterprise tier, with an open-source self-hosted core.

3. Does TrustGate ship pre-built MCP servers?

No. NeuralTrust's documentation states TrustGate is not an MCP connectivity platform and does not ship a library of pre-built MCP integrations; it governs the servers the customer registers.

4. Which AI gateway is better for enterprise AI?

Neither is universally better. Security-led buyers wanting a first-party enforcement engine and multi-turn analysis tend toward TrustGate; Kubernetes-native enterprises wanting one sovereign control plane for models, agents, and tools tend toward TrueFoundry.

5. Does either gateway do AI posture management (AI-SPM)?

Not as a gateway feature. NeuralTrust offers a separate posture product (TrustLens) aimed at AI across the estate, including AI outside the gateway; TrueFoundry centers governance on the traffic and workloads running on its platform rather than a separate discovery product.

6. How does TrueFoundry handle runtime security?

Through a configurable guardrails framework on input and output paths: built-in PII/PHI, secrets, prompt-injection and toxicity checks, plus integrations with OpenAI Moderation, AWS Guardrails, and Azure Content Safety, and custom rules as configuration or Python. It is not positioned as a dedicated first-party multi-turn behavioral detection engine.

7. Is TrueFoundry open source?

TrueFoundry is a commercial enterprise platform with usage-based pricing that integrates open-source components (for example KubeElasti, and, after its June 2026 acquisition, Seldon Core). Third-party analysis notes that TrueFoundry tends to include governance features as standard rather than gating them behind higher tiers, but the platform itself is commercial.

8. Does TrueFoundry have an MCP gateway?

Yes. TrueFoundry's MCP Gateway provides a central registry, unified endpoint, per-server and tool-level RBAC, OAuth 2.0, and federated identity (Okta, Azure AD), plus prebuilt connectors for tools like Slack, GitHub, Confluence, and Datadog, and the ability to register custom MCP servers.

9. Can TrueFoundry serve self-hosted models?

Yes. TrueFoundry serves self-hosted and open-source models (LLaMA, Mistral, and others) with backends such as vLLM, SGLang, Triton, and KServe, behind the same gateway that routes hosted models. This is a capability outside the scope of a pure gateway like TrustGate.

10. What did TrueFoundry acquire in June 2026?

TrueFoundry acquired Seldon AI (announced June 24, 2026), a UK-based MLOps platform whose open-source Seldon Core provides real-time ML serving, A/B testing, canary rollouts, and observability, adding a traditional-ML serving foundation to TrueFoundry's control plane.

11. Which has better data sovereignty?

Both keep data inside the customer's infrastructure. TrueFoundry's edge is that it is fully self-hosted, cloud-agnostic, and Kubernetes-native, running the entire hot path inside the customer's cluster with physical tenant isolation via namespaces. TrustGate offers VPC and air-gapped deployment at its enterprise tier.

12. Do I need Kubernetes to use TrueFoundry?

TrueFoundry is Kubernetes-native and its architecture assumes a Kubernetes operating model, which is ideal for teams already on Kubernetes. Teams that do not run Kubernetes should weigh the operational commitment. TrustGate is a focused AI gateway that does not require adopting a Kubernetes-centric platform.

13. Which has better observability?

Both are strong. TrueFoundry provides OpenTelemetry-native metrics, traces, and full request/response logging, exportable to Grafana, Datadog, and Prometheus. TrustGate emphasizes a single unified multi-protocol trace tree with cost, latency, and security findings attributed inline in the same view.

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About the Author

Alessandro Pignati is Lead AI Security Researcher at NeuralTrust, where he leads research on AI and agentic security, advancing techniques to evaluate and secure large language models and autonomous AI systems. He specializes in adversarial machine learning, AI red teaming, LLM security, and AI safety, contributing to the development of secure and trustworthy AI.

NeuralTrust is an AI agent security platform, recognized in the Gartner 2025 Market Guide for Guardian Agents. Headquartered in Barcelona with ISO 27001 certification.