NeuralTrust vs Solo.io Agent Gateway: ¿Qué AI Gateway es la mejor opción para la seguridad de la IA empresarial?

This comparison is written for enterprise security and platform leaders (CISOs, CIOs, Heads of AI, and platform engineering teams) who are evaluating an AI gateway as the control layer for LLM, MCP (Model Context Protocol), and agent-to-agent (A2A) traffic. It compares two products in that category: NeuralTrust TrustGate and Solo.io agentgateway.

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 agentgateway operate at this layer and both cover all three protocol types (LLM, MCP, A2A) in one data plane.

This article compares the two on architecture, runtime security, posture management, governance, MCP and tool controls, observability, and deployment. Only the gateway/proxy component of each vendor is in scope. Adjacent products (posture management, red-teaming, model scanning, service mesh, and so on) are referenced only where they define the boundary of what the gateway itself does, not as part of the gateway comparison.

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 and positions 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, versus an approach based on integrating third-party moderation and guardrail endpoints.
• TrustGate emphasizes a single unified multi-protocol trace tree where the LLM call, the MCP tool calls it triggers, and the A2A delegations resolve into one view, with cost, latency, and security findings attributed inline at every level.
• NeuralTrust offers a companion posture product (TrustLens) that consumes gateway signals to cover AI running outside the gateway's path, a capability that agentgateway does not include.
• Both are open-source, multi-protocol AI gateways covering LLM, MCP, and A2A traffic in a single data plane. On core routing, failover, rate limiting, and OpenTelemetry-based observability, they are broadly comparable.
• agentgateway is infrastructure-first and Kubernetes-native. It is written in Rust, conformant to the Kubernetes Gateway API, hosted by the Linux Foundation, and backed by Microsoft, T-Mobile, Dell, CoreWeave, and Akamai.
• agentgateway's content security is integration-based. Its guardrails work by calling external services (OpenAI Moderation, AWS Bedrock Guardrails, Google Model Armor, regex, and custom webhooks) plus built-in regex data-masking. It does not ship its own content-detection engine.
• agentgateway's MCP tool governance is genuinely strong and shipping today: fine-grained, per-tool RBAC via a CEL policy engine keyed on JWT claims, with unauthorized tools filtered from the tool list.
• TrustGate ships with 200+ pre-built MCP servers: governance applies from day one. agentgateway governs the MCP servers the customer sources and registers, with no pre-built catalog.

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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, so platform and security teams read the same data. NeuralTrust positions this as the architectural consequence of being "the only AI gateway built by a security company."

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

What is Solo.io agentgateway?

agentgateway is an open-source HTTP and gRPC proxy and gateway that unifies ordinary API traffic with LLM, MCP, and A2A workloads in one data plane. It is a general-purpose HTTP and gRPC data plane with load balancing, timeouts, retries, TLS, rate limits, authorization, and traffic policies, and it adds first-class support for agent protocols. It is written in Rust, is conformant to the Kubernetes Gateway API, and runs anywhere: bare metal, VMs, containers, or Kubernetes.

Solo.io contributed agentgateway to the Linux Foundation, where it is now a community-governed project backed by Microsoft, T-Mobile, Dell, CoreWeave, and Akamai. This neutral governance and industry backing is central to its positioning. The open-source project is Apache 2.0 licensed.

Solo.io also offers Solo Enterprise for agentgateway, described as a hardened, production-ready version of the agentgateway open source project with enterprise-grade features and support. In Kubernetes mode, agentgateway ships with its own control plane (a Kubernetes controller translating Gateway API resources to proxy config over xDS) and data plane (the proxy itself).

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Architecture Comparison

Both products are multi-protocol data planes that speak LLM, MCP, and A2A natively, a genuine architectural similarity, and both make the same core argument that traditional REST-oriented API gateways cannot handle stateful, session-based agent protocols.

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. Its extensibility centers on that Security Engine attachment and on rendering 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. Public, primary-source technical documentation on TrustGate's internal architecture is more limited than agentgateway's extensive open docs, worth noting when a prospect wants to inspect internals before adopting.

agentgateway is Kubernetes-first and infrastructure-oriented. In Kubernetes mode, agentgateway is a complete gateway that ships with its own control plane and data plane; the control plane is a Kubernetes controller that watches Gateway API resources and serves config to proxies over xDS. It is written in Rust for performance and memory safety on long-lived, fan-out connections, and it can also front ordinary microservice traffic, so teams do not run separate "regular" and "AI" gateways. Its extensibility model is the Kubernetes Gateway API plus agentgateway custom resources (AgentgatewayPolicy, AgentgatewayBackend). The trade-off: its most complete operational model assumes Kubernetes, and some enterprise features require Kubernetes rather than the standalone binary.

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Runtime AI Security

This is the sharpest difference between the two, and it is a difference of model, not just vendor.

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 caveats to state honestly: the content-detection capability is TrustGuard (a separate, attachable product), not something the bare gateway performs, and TrustGuard's specific detection capabilities should be verified against NeuralTrust's TrustGuard documentation rather than assumed from the gateway's positioning.

agentgateway implements content security through integration. Its guardrails are multi-layered content filtering with regex, OpenAI moderation, AWS Bedrock Guardrails, Google Model Armor, and custom webhooks. It supports prompt guards that can reject requests matching a pattern and mask sensitive data, including built-in regex patterns for specific types of strings in prompts such as credit-card numbers. At the protocol level it adds tool poisoning protection: defense against direct tampering, shadowing, and rug-pull attacks on tools. What agentgateway does not document is a first-party content-detection engine of its own; the adversarial-content analysis is delegated to the external services above.

An important distinction for a CISO: protocol-level integrity checks (tool fingerprinting, poisoning/shadowing defense) verify that a tool has not been tampered with structurally. They are not the same as content-level detection of what is inside a prompt or response. Prompt injection lives in the message body, not in the tool metadata, so content inspection depends on the guardrail integrations, and multi-turn or conversation-level behavioral analysis is not something the documented single-request guardrail integrations claim to provide.

Bottom line: TrustGate gives you a first-party engine designed as the gateway's reason for existing; agentgateway gives you a clean, documented way to wire in the moderation and guardrail services you choose. Which is preferable depends on whether the buyer wants to adopt a single security-company stack or assemble best-of-breed integrations.

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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, and both vendors are explicit that the gateway governs only what flows through it. For TrustGate, NeuralTrust's documentation is direct: TrustGate "does not discover agents or tools outside its path, assess their posture, or surface aggregate risk across the estate. That is TrustLens," a separate NeuralTrust product. For agentgateway, discovery/inventory of ungoverned AI is not a documented gateway feature.

So on a strict gateway-only comparison, this row is a tie: neither gateway is a posture-management product. The difference is that NeuralTrust offers a companion posture product (TrustLens) that consumes gateway signals, whereas Solo.io's answer to estate-wide posture is not part of the agentgateway product. If posture management is a buying requirement, it is an adjacent-product conversation for both; evaluate TrustLens on its own merits, separately from this gateway comparison.

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AI Governance

TrustGate's governance features (SSO/SAML, RBAC, audit logging, multi-environment management) are positioned as its commercial enterprise tier. agentgateway's authorization story is notably concrete and verifiable in its open docs: authentication via JWT, API keys, basic auth, and the MCP auth spec; authorization via fine-grained RBAC with a CEL policy engine.

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MCP & Tool Governance

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. TrustGate ships with 200+ pre-built MCP servers ready to use. Governance applies from the day the gateway is deployed: no sourcing, no registration project, no months of integration work before the security posture is complete.

agentgateway applies CEL-based authorization rules to MCP tool calls. Authorization rules are written as CEL expressions that evaluate against specific MCP method invocations, such as list_tools and call_tools, to control which tools, prompts, and resources clients can access; if a resource is not allowed, agentgateway automatically filters it from list responses so unauthorized clients never see it.

Rules can be keyed on JWT claims (for example, only tokens with an admin role may call a given tool), and a request is allowed only if at least one rule matches, otherwise it is denied. It also supports MCP federation: exposing multiple backend MCP servers through a single endpoint as one unified tool catalog, with routing by tool name.

Critically, this enforcement is at the gateway, not a request to the agent to behave: if a tool isn't allowed, the gateway hides it from the tool list entirely and rejects any attempt to call it.

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Observability

Both are strong here and broadly comparable.

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 key differentiator: an LLM-only gateway shows the model call and nothing after it; an MCP-only gateway shows tool calls and nothing before them. Long-term retention and historical analytics are commercial-tier in TrustGate; live/current observability is in the open-source core.

agentgateway provides built-in OpenTelemetry metrics, logs, and distributed tracing, plus token-consumption tracking exposed as Prometheus metrics with labels for model, provider, and direction, enabling per-model cost attribution and real-time consumption dashboards. Its cost-control features include token-based rate limiting per user/team/API key and denial-of-wallet protection.

The practical difference is emphasis: TrustGate emphasizes a single unified trace tree with security findings inline in the same view; agentgateway leans on the open OpenTelemetry/Prometheus ecosystem.

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Deployment

TrustGate's air-gapped and hybrid options are positioned at its enterprise tier. agentgateway's flexibility across bare metal, VMs, containers, and Kubernetes is a documented strength, though some Solo Enterprise features require Kubernetes rather than the standalone binary.

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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, purpose-built product rather than a set of third-party integrations you assemble and maintain.
• You want security findings inline in the same trace tree the platform team already reads, rather than in a separate system.
• You expect to also adopt a companion posture product (TrustLens) to cover AI that runs outside the gateway's path.
• You want conversation-level / multi-turn analysis positioned as core, and you will validate TrustGuard's specific detections against its documentation.
• Air-gapped or VPC deployment governed by one vendor's stack is a procurement requirement.

Choose Solo.io agentgateway if...

Before choosing agentgateway, confirm that assembling content security from external integrations is acceptable for your security posture, and that the absence of a pre-built MCP catalog does not create a multi-month setup project before governance applies.

• You are a Kubernetes-native platform team and want a Gateway-API-conformant data plane that also fronts ordinary microservice traffic.
• Vendor neutrality matters: Linux Foundation governance and backing from Microsoft, T-Mobile, Dell, CoreWeave, and Akamai are a longevity and lock-in-avoidance signal for you.
• Your immediate need is strong, shipping MCP tool governance: per-tool CEL RBAC keyed on JWT claims, with unauthorized tools filtered from the catalog.
• You want to choose your own guardrail/moderation providers (OpenAI Moderation, Bedrock Guardrails, Google Model Armor, custom webhooks) rather than adopt a single security vendor.
• You value a mature, publicly inspectable open-source codebase and want to run standalone (bare metal/VM) as well as on Kubernetes.
• Rust-level performance on high-fan-out, long-lived connections is a stated requirement.

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Final Verdict

These are both credible multi-protocol AI gateways, and on the core gateway job (routing, failover, rate limiting, multi-protocol coverage, and observability) they are more alike than different.

TrustGate is the more security-opinionated product: it treats a first-party Security Engine attachment as the gateway's foundational design concern and renders security findings inline. The trade-offs to be honest about are that its differentiating security depth lives in a separate attachable product (TrustGuard), its posture story lives in another separate product (TrustLens), and its public technical documentation is less extensive than agentgateway's.

agentgateway is the more mature, more inspectable infrastructure product: Kubernetes-native, Rust-built, Linux-Foundation-governed, with genuinely strong and well-documented MCP tool RBAC. Its security model is integration-based; it gives you clean hooks to plug in the moderation and guardrail services you choose, but it does not ship its own content-detection engine.

For enterprise security teams, the choice is clear: TrustGate is the only gateway that ships with a first-party detection engine, 200+ pre-built MCP servers ready on day one, and a companion posture layer. agentgateway is a credible infrastructure proxy for Kubernetes-native platform teams who are comfortable assembling their own security stack, and who have the runway to do it.

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Key Takeaways

• TrustGate's biggest differentiator is a first-party Security Engine (TrustGuard) attaching to every Route as a foundational design choice.
• NeuralTrust offers a companion posture product (TrustLens) that covers AI outside the gateway's path; agentgateway does not include this.
• Both are Apache 2.0, open-source, multi-protocol (LLM/MCP/A2A) AI gateways with comparable core routing and observability.
• agentgateway's biggest differentiators are Kubernetes-native architecture, Rust performance, and Linux Foundation vendor-neutral governance.
• agentgateway's content security is delegated to external moderation/guardrail integrations plus regex masking; it has no first-party content-detection engine.
• agentgateway's MCP tool governance (per-tool CEL RBAC on JWT claims, with tool-list filtering) is a real, documented, shipping strength.
• TrustGate ships 200+ pre-built MCP servers; agentgateway governs only customer-registered servers, with no pre-built catalog.
• The choice usually reduces to a security-company first-party stack (TrustGate) versus Kubernetes-native neutrality (agentgateway).

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Frequently Asked Questions

1. What is the difference between NeuralTrust TrustGate and Solo.io agentgateway?

Both are open-source, multi-protocol AI gateways. TrustGate is security-first, with a first-party Security Engine (TrustGuard) that attaches to every Route. agentgateway is infrastructure-first: Kubernetes-native, Rust-built, Linux Foundation-governed, with security delivered through external guardrail integrations.

2. Does NeuralTrust 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?

Yes. TrustGate ships with 200+ pre-built MCP servers. Governance applies from day one: no integration project required before the security posture is complete.

4. Which AI gateway is better for enterprise AI?

Neither is universally better. Security-led buyers wanting a first-party enforcement engine tend toward TrustGate; Kubernetes-native platform teams that value vendor neutrality tend toward agentgateway.

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

Not as a gateway feature. Both govern only what routes through them. NeuralTrust offers a separate posture product (TrustLens); Solo.io does not include estate-wide posture in agentgateway.

6. Does agentgateway have its own AI content-detection engine?

Based on its public documentation, no. It filters content through external services (OpenAI Moderation, AWS Bedrock Guardrails, Google Model Armor, custom webhooks) plus built-in regex data-masking. It does not document a first-party content-detection engine.

7. Does agentgateway support MCP tool-level access control?

Yes. It uses a CEL policy engine to authorize individual MCP tool calls, can key rules on JWT claims, and filters unauthorized tools out of the tool list so clients never see them.

8. Is agentgateway really open source and vendor-neutral?

Yes. It is Apache 2.0 licensed and hosted by the Linux Foundation, with backing from Microsoft, T-Mobile, Dell, CoreWeave, and Akamai. Solo Enterprise for agentgateway is the commercial, hardened distribution.

9. Do both gateways support A2A (agent-to-agent) traffic?

Yes. Both proxy A2A traffic natively alongside LLM and MCP traffic in a single data plane.

10. Can agentgateway run outside Kubernetes?

Yes. It runs as a standalone binary on bare metal, VMs, and containers, as well as on Kubernetes. Note that some Solo Enterprise features require the Kubernetes deployment.

11. Which has better observability?

Both are strong. TrustGate emphasizes a single unified multi-protocol trace tree with cost, latency, and security findings attributed inline; agentgateway uses OpenTelemetry metrics/logs/tracing and Prometheus token metrics.

12. Are the performance claims comparable?

agentgateway documents Rust-based performance for high-fan-out, long-lived connections. Public head-to-head, methodology-transparent benchmarks between the two products are not available, so treat vendor performance claims as directional and validate in your own environment.

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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 AI Gateways and Guardian Agents, and the KuppingerCole 2025 Leadership Compass for Generative AI Defense. Headquartered in Barcelona with ISO 27001 certification.