NeuralTrust vs HAProxy: 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 and agent traffic. It compares two products in that category: NeuralTrust TrustGate and the HAProxy AI Gateway.

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

The two products approach the category from different starting points. TrustGate is built by a security company and treats runtime AI security enforcement as the gateway's organizing principle. HAProxy is one of the world's fastest and most widely used software load balancers and reverse proxies, and its AI Gateway is a capability of HAProxy Enterprise (the data plane) managed through HAProxy Fusion (the control plane), extending a proven application-delivery and security platform into AI traffic.

This article compares them on architecture, runtime security, posture management, governance, MCP and tool controls, observability, and deployment. Only the AI gateway component is in scope.

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 AI runtime detection engine. HAProxy delivers AI security primarily through its Enterprise WAF, which inspects each prompt for safety, data loss, and routing, rather than a dedicated first-party AI content-detection engine built for multi-turn behavioral analysis.
• NeuralTrust offers a companion posture product (TrustLens) that discovers and assesses AI running outside the gateway's path, a layer HAProxy does not include.
• TrustGate emphasizes a single unified multi-protocol trace tree across LLM, MCP, and A2A traffic, with cost, latency, and security findings attributed inline.
• HAProxy is a best-in-class, extremely high-performance load balancer and ADC with a mature, battle-tested security stack (WAF, DDoS protection, bot management, SSL/TLS) and proven scale. For teams that already run HAProxy, extending it to AI traffic is a natural, low-friction step.
• HAProxy's AI Gateway is delivered through HAProxy Enterprise plus HAProxy Fusion. The core AI gateway capabilities (WAF-based prompt inspection, token-based rate limiting via the Global Profiling Engine, 150+ metrics in Fusion) are enterprise features, though HAProxy also has a widely used open-source community edition.
• HAProxy's strengths are performance, WAF-grade security, rate limiting, prompt-based routing, and deploy-anywhere flexibility (any cloud or Kubernetes, no lock-in).
• MCP and A2A governance are not documented AI gateway features for HAProxy today; its AI focus is cost control, WAF-based prompt security, routing, and observability for LLM traffic.

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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 the HAProxy AI Gateway?

HAProxy is the world's fastest and widely used software load balancer and reverse proxy, and a category leader in API management, WAF, DDoS protection, bot management, and load balancing. Its AI Gateway is not a separate AI-native product but a capability of the HAProxy One platform: HAProxy Enterprise serves as the data plane (high-performance load balancing, API/AI gateway, SSL processing, multi-layered security), HAProxy Fusion serves as the control plane (management, monitoring, automation across clusters, clouds, and teams), and HAProxy Edge provides a global edge network.

As an AI gateway, HAProxy provides token-based rate limiting to control LLM query volume and prevent excessive token consumption (with granular ACL expressions synchronized across HAProxy Enterprise clusters via the Global Profiling Engine), prompt-based routing (the HAProxy Enterprise WAF inspects each prompt to evaluate safety, prevent data loss, and determine routing behaviors), and centralized observability (150+ performance, security, and query-specific metrics in HAProxy Fusion, including prompt inspection, prompt sizes, and query rates). HAProxy also supports intermediate API-key strategies so application developers never handle the real provider key values directly, and it can detect sensitive data such as social security and credit card numbers in prompts.

The key context: HAProxy's AI Gateway is the application of a best-in-class load balancer and security ADC to AI traffic. Its documented AI capabilities center on cost control, WAF-based prompt security, routing, and observability, and they are delivered through HAProxy Enterprise and HAProxy Fusion (HAProxy also maintains a widely used open-source community edition, though the AI gateway capabilities described here are enterprise features). It can be deployed in any cloud or Kubernetes infrastructure without lock-in.

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Architecture Comparison

Both are software gateways that centralize AI traffic and apply policy in the request path, and both are known for performance.

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 with AI security as the organizing principle.

HAProxy inherits a proven, extremely high-performance data plane. The AI gateway runs on HAProxy Enterprise as the enforcement point, with HAProxy Fusion as the control plane for management, monitoring, and automation across multi-cluster, multi-cloud, and multi-team deployments. Rate limiting uses HAProxy's stick tables, and the Global Profiling Engine aggregates client activity across an active/active cluster so limits (for example token-per-minute quotas) hold consistently across load balancers. Prompt inspection is performed by the HAProxy Enterprise WAF. The strengths are raw performance, maturity, and a unified platform where AI traffic is governed with the same engine that already handles APIs, load balancing, SSL, and security. The trade-off is orientation: HAProxy approaches AI as an extension of application delivery and WAF-based security, so AI-specific abstractions (a dedicated AI content-detection engine, MCP and A2A governance) are not the platform's native model today.

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Runtime AI Security

This is the sharpest 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.

HAProxy delivers AI runtime security primarily through the HAProxy Enterprise WAF, which inspects each prompt to evaluate safety, prevent data loss, and determine routing behavior, and can detect sensitive data such as social security and credit card numbers before it leaves the customer's infrastructure. This is backed by HAProxy's broader multi-layered security (DDoS protection, bot management, and a WAF that customers praise for low latency and a low false-positive rate). It is a genuinely strong, battle-tested security stack. The distinction for an AI security buyer: HAProxy's AI protection is grounded in WAF-based prompt inspection and its mature web-application security controls, rather than a first-party AI detection engine purpose-built for LLM-specific threats, and multi-turn behavioral analysis of adversarial intent across a conversation is not positioned as a dedicated capability.

Bottom line: TrustGate offers a first-party AI detection engine from a security company, attached inline as the gateway's organizing principle, with multi-turn analysis positioned as core. HAProxy offers a mature, high-performance WAF-based security model that inspects prompts for safety and data loss within a best-in-class ADC. Which fits depends on whether the buyer wants a dedicated AI-native detection stack or wants AI traffic protected by the same proven WAF and security platform that already guards their APIs.

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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 HAProxy, estate-wide AI discovery and posture assessment is not a documented capability; HAProxy governs and observes the traffic that flows through it.

On a strict gateway-only basis this is a tie: neither gateway is a posture-management product. The practical difference is that NeuralTrust offers a dedicated companion posture product (TrustLens) aimed at the full AI estate, whereas HAProxy has no equivalent companion layer for discovering ungoverned AI.

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AI Governance

HAProxy's governance is grounded in its API-management and ADC heritage. Its cost and access controls are notably strong: token-based rate limiting enforced consistently across an active/active cluster via the Global Profiling Engine, granular ACL expressions synchronized across HAProxy Enterprise, and API-key protection through hashing, per-key quotas, intermediate-key strategies (developers never touch the real provider key), and instant revocation without contacting the upstream provider. HAProxy Fusion provides centralized, multi-team management across clusters and clouds. TrustGate reserves SSO/SAML, RBAC, and long-term retention for its enterprise tier. Both deliver enterprise governance; HAProxy's differentiator is cluster-consistent rate limiting and key protection at scale, while TrustGate's is security findings as first-class spans in the trace.

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MCP & Tool Governance

This is an area of clear difference.

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. It also covers A2A (agent-to-agent) traffic alongside LLM and MCP.

HAProxy does not document MCP governance or A2A traffic as AI gateway features today. Its AI Gateway focuses on LLM traffic: token-based rate limiting, WAF-based prompt inspection, prompt-based routing, and observability. HAProxy could, as a general-purpose high-performance proxy, route MCP or agent HTTP traffic like any other traffic, but tool-level MCP governance (per-consumer tool allowlists, tool-call auditing) and A2A are not part of its documented AI gateway capability set.

For a buyer whose roadmap includes agentic architectures with MCP tool governance and agent-to-agent traffic, this is a meaningful gap for HAProxy relative to TrustGate. Confirm current capabilities against HAProxy's documentation if this is a requirement.

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Observability

Both provide strong observability, and observability is a HAProxy strength.

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.

HAProxy provides centralized observability through HAProxy Fusion, exposing 150+ performance, security, and query-specific metrics, including prompt inspection, prompt sizes, and query rates per second, for troubleshooting, security implementation, and capacity planning. It also offers flexible logging of token usage (prompt and completion tokens) into standard HAProxy logs or asynchronous real-time funneling to external endpoints such as Grafana or a TimescaleDB HTTP endpoint. This is mature, high-scale observability from a platform built to monitor very high traffic volumes.

The practical difference is emphasis: TrustGate centers a unified multi-protocol trace with security findings inline in the same view; HAProxy centers deep operational and security metrics in Fusion, integrated with the same platform that already monitors an organization's APIs and load balancers.

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Deployment

HAProxy's deployment flexibility is a genuine strength: deploy anywhere, in any cloud or Kubernetes infrastructure, with no vendor lock-in, managed centrally across clusters and clouds through HAProxy Fusion, and with a global edge network available through HAProxy Edge. HAProxy is also known for running some of the highest-traffic infrastructure in the world. TrustGate positions air-gapped and hybrid at its enterprise tier and keeps data inside the customer's perimeter. Both suit data-residency-sensitive buyers; HAProxy's edge is proven performance and operational maturity at extreme scale, while TrustGate's is a security-first enforcement model with an attachable AI detection engine.

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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, AI-native product from a security company, engineered as the gateway's reason for existing rather than WAF-based prompt inspection.
• 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 need MCP tool governance and A2A (agent-to-agent) coverage as first-class capabilities in the same gateway.
• You want a purpose-built AI gateway rather than an ADC and WAF platform extended to AI traffic.

Choose HAProxy if...

• You already run HAProxy for load balancing, API management, or WAF, and you want AI traffic governed on the same proven, high-performance platform.
• You need best-in-class performance and scale and value HAProxy's track record on some of the highest-traffic infrastructure in the world.
• Your primary AI concerns are cost control, WAF-based prompt security, prompt-based routing, and observability for LLM traffic, rather than MCP or A2A governance.
• You want cluster-consistent token rate limiting and strong API-key protection (hashing, intermediate keys, instant revocation).
• You value deploy-anywhere flexibility (any cloud or Kubernetes, no lock-in) with centralized multi-team management through HAProxy Fusion.
• You trust a mature, battle-tested WAF as your primary AI security control and do not require a dedicated AI-native detection engine today.

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Final Verdict

Both are credible choices, and both keep data inside the customer's infrastructure, but they come from different worlds. HAProxy's advantages are performance, maturity, and platform consolidation: a best-in-class load balancer and security ADC whose AI Gateway brings token-based rate limiting, WAF-based prompt inspection, prompt-based routing, strong API-key protection, and deep observability to AI traffic, all managed on the same platform that already runs an organization's APIs and load balancers, deployable anywhere without lock-in. TrustGate's advantages are AI-native security depth: a first-party Security Engine attached inline, multi-turn analysis positioned as core, MCP tool governance, A2A coverage, unified multi-protocol tracing with security findings in the same view, and a companion posture product.

The decision usually turns on two axes. The first is the security model: TrustGate treats a first-party, AI-native Security Engine as the gateway's reason for existing, while HAProxy protects AI traffic with its mature, high-performance WAF and multi-layered security stack. The second is scope and heritage: HAProxy is the natural choice for organizations that prize performance, operational maturity, and consolidating AI onto an already-trusted ADC platform, especially those already running HAProxy, whereas TrustGate is a purpose-built, security-first AI gateway with AI-native abstractions (a detection engine, MCP and A2A governance, a posture companion).

A security-led buyer who wants an AI-native enforcement substrate with multi-turn analysis, MCP and A2A coverage, and a posture companion will likely prefer TrustGate. An organization standardized on HAProxy that wants proven performance and to govern AI traffic with the same WAF and platform that already protects its APIs will likely prefer HAProxy.

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Key Takeaways

• TrustGate's biggest differentiators are a first-party, AI-native Security Engine (TrustGuard) with multi-turn analysis, unified multi-protocol tracing including A2A with inline security findings, MCP tool governance, and a companion posture product (TrustLens).
• HAProxy is one of the world's fastest and most widely used load balancers and security ADCs; its AI Gateway is a capability of HAProxy Enterprise plus HAProxy Fusion, not a separate AI-native product.
• HAProxy's AI runtime security is WAF-based: the HAProxy Enterprise WAF inspects each prompt for safety, data loss, and routing, rather than a first-party AI detection engine built for multi-turn analysis.
• HAProxy's strengths are performance, cluster-consistent token-based rate limiting (Global Profiling Engine), strong API-key protection, prompt-based routing, and 150+ metrics in HAProxy Fusion.
• MCP governance and A2A traffic are not documented AI gateway features for HAProxy today; TrustGate covers both.
• HAProxy deploys anywhere (any cloud or Kubernetes, no lock-in) and maintains a widely used open-source community edition, with the AI gateway capabilities delivered via HAProxy Enterprise.
• Both keep data inside the customer's infrastructure; TrustGate offers an open-source core with a commercial enterprise tier.
• The choice usually reduces to an AI-native, security-first gateway (TrustGate) versus AI traffic governed by a best-in-class, high-performance ADC and WAF platform (HAProxy).

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Frequently Asked Questions about NeuralTrust vs HAProxy

1. What is the difference between NeuralTrust TrustGate and the HAProxy AI Gateway?

TrustGate is a security-first, purpose-built AI gateway whose Security Engine (TrustGuard) attaches to every Route and which covers LLM, MCP, and A2A traffic with inline security findings. The HAProxy AI Gateway is a capability of HAProxy Enterprise (data plane) and HAProxy Fusion (control plane) that applies a best-in-class load balancer and WAF to AI traffic, with security delivered through WAF-based prompt inspection rather than a first-party AI detection engine.

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, AI-native detection engine with MCP and A2A coverage tend toward TrustGate; organizations standardized on HAProxy that prize performance and want AI protected by the same WAF and platform as their APIs tend toward HAProxy.

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

Not as a gateway feature. NeuralTrust offers a separate posture product (TrustLens) that covers AI outside the gateway's path; HAProxy has no equivalent companion layer.

6. How does HAProxy handle AI runtime security?

Primarily through the HAProxy Enterprise WAF, which inspects each prompt to evaluate safety, prevent data loss, and determine routing behavior, and can detect sensitive data such as social security and credit card numbers. This is backed by HAProxy's broader multi-layered security (DDoS protection, bot management). It is not a first-party AI content-detection engine built for LLM-specific, multi-turn behavioral analysis.

7. Is the HAProxy AI Gateway open source?

HAProxy maintains a widely used open-source community edition of its load balancer. The AI Gateway capabilities described on HAProxy's solution page (WAF-based prompt inspection, cluster-consistent token rate limiting via the Global Profiling Engine, and 150+ metrics in HAProxy Fusion) are delivered through HAProxy Enterprise and HAProxy Fusion, which are commercial products.

8. Does HAProxy support MCP or agent-to-agent (A2A) traffic?

MCP governance and A2A are not documented AI gateway features for HAProxy today. As a general-purpose high-performance proxy it can route such HTTP traffic, but tool-level MCP governance and A2A are not part of its documented AI gateway capability set. TrustGate covers MCP and A2A as first-class capabilities.

9. How does HAProxy control AI costs?

Through token-based rate limiting that caps prompt and response token consumption, enforced consistently across an active/active cluster via the Global Profiling Engine, plus granular ACL expressions and prompt-based routing that can send simpler queries to cheaper models. It also protects API keys with hashing, per-key quotas, and instant revocation.

10. Which has better observability?

Both are strong. HAProxy Fusion exposes 150+ performance, security, and query-specific metrics (including prompt inspection, prompt sizes, and query rates), with flexible token-usage logging to standard logs or external endpoints like Grafana. TrustGate emphasizes a single unified multi-protocol trace tree with cost, latency, and security findings attributed inline.

11. Is HAProxy a good fit if we already use it for load balancing?

Yes. That is HAProxy's strongest scenario: if you already run HAProxy for load balancing, API management, or WAF, extending it to AI traffic keeps the same performance, configurability, observability, and security platform, with no new system to operate and no vendor lock-in.

12. Do I need a dedicated AI security engine, or is a WAF enough?

It depends on your threat model. HAProxy's WAF-based prompt inspection is a mature, high-performance control for safety and data-loss concerns. If your requirements include LLM-specific, multi-turn behavioral analysis, MCP tool governance, and A2A coverage as first-class capabilities, a purpose-built AI security gateway such as TrustGate is designed for exactly that. Some organizations pair a strong WAF platform with a dedicated AI security layer.

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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.