NeuralTrust vs Helicone: 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 Helicone.

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 Helicone put LLM traffic behind a unified, self-hostable endpoint and give teams centralized monitoring and control.

The two products approach the category from different starting points. TrustGate is built by a security company and treats runtime security enforcement as the gateway's organizing principle. Helicone is an open-source LLM observability platform and AI gateway, popular for a famously simple single-URL integration, that pairs a fast Rust-based proxy with a rich analytics and monitoring dashboard.

One current fact is essential context for any evaluation: Helicone was acquired by Mintlify on March 3, 2026, and the product is now in maintenance mode (security updates, bug fixes, and new models continue, but no new feature development). This article compares them on architecture, runtime security, posture management, governance, MCP and tool controls, observability, and deployment. Only the 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 runtime detection engine. Helicone's core is observability plus a routing, caching, and rate-limiting gateway; it does not provide a first-party AI content-detection engine or an inline guardrail layer for prompt-injection, PII, and jailbreak enforcement.
• NeuralTrust offers a companion posture product (TrustLens) that discovers and assesses AI running outside the gateway's path, a layer Helicone 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.
• Helicone is an excellent, developer-loved observability gateway. Its strengths are a one-line integration (change the base URL), a fast open-source Rust proxy ("the NGINX of LLMs"), access to 100+ models, response caching, rate limiting, automatic fallbacks, and a polished analytics dashboard, all Apache 2.0 and self-hostable.
• Helicone is in maintenance mode after the Mintlify acquisition (March 3, 2026). Security updates, bug fixes, and new models continue, but new feature development has stopped, which is a material procurement consideration for a multi-year roadmap.
• Helicone's center of gravity is observability and cost control, not runtime security or agentic governance. MCP appears only as a data-export server, and A2A is not a gateway feature.
• Both are Apache 2.0 and self-hostable; the difference is that TrustGate centers security enforcement and is actively developed as a security-first control plane, while Helicone centers observability and is now in maintenance mode.

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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 Helicone?

Helicone is an open-source LLM observability platform and AI gateway, launched out of Y Combinator (W23) and known for processing a very large volume of production traffic (the team cites trillions of tokens across roughly 16,000 organizations). Its signature feature is integration simplicity: instead of wrapping an LLM client in a new SDK, an application changes a single base URL and immediately gets logging, cost tracking, and gateway features. The AI gateway itself is open-source and built on Rust, described by the team as "the NGINX of LLMs," and provides access to 100+ models through an OpenAI-compatible interface with smart routing, automatic fallbacks, response caching (Helicone cites cost reductions of up to 90 percent through caching), and rate limiting.

Around the gateway sits Helicone's real center of gravity: a polished observability product with dashboards for requests, sessions, users, and traces, plus prompt management, datasets, scores, feedback, webhooks, and alerts. It is Apache 2.0, self-hostable with Docker or a production Helm chart, and its hosted service is SOC 2 and GDPR compliant with encryption in transit and at rest.

The essential current context: on March 3, 2026, the documentation company Mintlify acquired Helicone, and the founders joined Mintlify. Helicone continues to operate in maintenance mode, meaning security updates, bug fixes, and new model support keep shipping, but new feature development has stopped. The open-source project remains live under Apache 2.0 and the proxy still works, but a maintenance-mode status is a real consideration for any team building a multi-year dependency.

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Architecture Comparison

Both are self-hostable software gateways that centralize LLM access and are known for low latency, and both are Apache 2.0.

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 security as the organizing principle, and it is actively developed.

Helicone uses a two-part architecture: a lightweight Rust proxy on the request path (load balancing, rate limiting, caching, tracing, fallbacks) and an observability plane behind it (dashboard, monitoring, debugging), with object storage for logs. The request passes through the proxy, which logs the full request and response, tracks tokens and cost, and applies configured behaviors before forwarding to the provider, with a self-hosted overhead the team cites as under 1 millisecond. The design is elegant and the single-URL integration is genuinely frictionless. Two architectural considerations for an enterprise security review: in cloud mode all traffic passes through Helicone infrastructure (a data-residency consideration that self-hosting removes at the cost of operational burden), and, more importantly, the architecture is built to observe and route, not to enforce content security, so there is no inline detection engine in the path.

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Runtime AI Security

This is the sharpest difference, and it is a difference of purpose.

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.

Helicone is built for observability, routing, and cost control rather than runtime threat detection. Its security-relevant features are the operational controls a gateway provides (rate limiting per user, team, or API key, key management so provider keys are not scattered across code, caching, and complete request logging for audit), plus SOC 2 and GDPR compliance and encryption for the hosted service. What it does not provide is a first-party AI content-detection engine or an inline guardrail layer that blocks prompt injection, redacts PII, detects jailbreaks, and enforces tool-call policy under one policy engine. Independent 2026 reviews make this gap explicit: Helicone has request analytics, but not an integrated guardrail layer, and it is now in maintenance mode, so that gap is unlikely to be closed by new feature work. For a runtime security mandate, these are different classes of tool.

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 and active development behind it. Helicone offers operational controls and excellent observability, without an inline detection or guardrail layer, and in maintenance mode. If runtime AI security is the requirement, TrustGate is built for it and Helicone is not.

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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 Helicone, estate-wide AI discovery and posture assessment is not a capability; Helicone observes and governs the traffic that flows through its proxy.

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 Helicone has no equivalent companion layer, and its maintenance-mode status means one is unlikely to appear.

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AI Governance

Helicone's governance strengths are operational and cost-oriented: fine-grained rate limits per user, team, or API key; centralized provider-key management so keys are not scattered across application code; caching to control spend; and complete request logging with dashboards and webhook alerts. These are useful controls, delivered with Helicone's characteristic simplicity. The limits for an enterprise security review are that deeper controls (native Slack or email alerting, some advanced features) sit on higher tiers, and that governance here means operational and financial governance rather than security policy enforcement. TrustGate reserves SSO/SAML, RBAC, and long-term retention for its enterprise tier and adds security enforcement via an attached engine. Both log everything; TrustGate's differentiator is security findings as first-class spans, while Helicone's is a polished, low-friction analytics experience.

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

Helicone does not provide MCP tool governance as a gateway feature. Where MCP appears in Helicone, it is as a data-management server that lets users access and export their Helicone data through MCP, which is the inverse of governing agents' MCP tool calls. A2A is not a Helicone gateway feature either. Helicone's gateway is focused on LLM provider traffic (routing, caching, rate limiting, observability), not on governing agentic tool use or agent-to-agent communication.

For a buyer whose roadmap includes agentic architectures with MCP tool governance and A2A traffic, this is a meaningful gap for Helicone relative to TrustGate, and the maintenance-mode status makes it unlikely to change.

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Observability

Observability is Helicone's genuine strength, and it is where the two products are closest in quality even as they differ in emphasis.

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.

Helicone offers a mature, developer-loved observability product: dashboards for requests, sessions, users, and traces; cost and latency tracking across the whole stack; caching analytics; prompt management with versioning; datasets, scores, and feedback for evaluation; and webhooks and alerts. It captures a structured log line per request with very low overhead and is frequently praised for making LLM usage immediately visible with almost no integration effort. Independent reviews note that its logs are request-centric rather than a deep span tree, so reconstructing complex multi-step agent traces and joining evaluation scores can be less rich than in span-native tracing tools, and that it lacks infrastructure-level metrics such as GPU monitoring.

The practical difference is emphasis: TrustGate centers a unified multi-protocol trace with security findings inline in the same view; Helicone centers best-in-class, low-friction request analytics and cost visibility for LLM traffic.

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Deployment

Helicone's deployment is flexible and developer-friendly: a hosted cloud for zero-ops adoption, or self-hosting with Docker Compose or a production Helm chart under Apache 2.0, keeping data under the customer's control. The hosted service is SOC 2 and GDPR compliant with encryption in transit and at rest. Two considerations: in cloud mode traffic passes through Helicone infrastructure (a data-residency point that self-hosting resolves), and self-hosting a maintenance-mode product means owning more of the operational burden over time. TrustGate positions air-gapped and hybrid at its enterprise tier and keeps data inside the customer's perimeter. Both are self-hostable; the differentiators are TrustGate's active development and security-first model versus Helicone's simplicity and maturity in maintenance mode.

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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 absent from the request path.
• 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.
• You want a gateway that is actively developed as a long-term, security-first control plane.

Choose Helicone if...

• You want the simplest possible integration (a single base-URL change) to get LLM observability, cost tracking, caching, and routing immediately.
• Your primary needs are request analytics, cost visibility, caching, rate limiting, and multi-provider routing, not runtime security or agentic governance.
• You value a fast, open-source Rust proxy and a polished, developer-loved analytics dashboard.
• You want an Apache 2.0, self-hostable tool you fully control, and you are comfortable owning the operational burden of a product in maintenance mode.
• You are building LLM applications (chatbots, content generation, summarization) rather than agentic systems needing MCP and A2A governance.
• You are already in the Mintlify ecosystem or comfortable with Helicone's current maintenance-mode status for your roadmap.

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Final Verdict

Both are open-source, self-hostable, low-latency gateways, and on multi-provider routing, caching, rate limiting, and observability they are genuinely comparable, with Helicone especially strong on integration simplicity and analytics polish. But they solve different primary problems, and two facts should anchor the decision. First, Helicone's center of gravity is observability and cost control, with no first-party detection engine or inline guardrail layer, whereas TrustGate's reason for existing is runtime AI security. Second, Helicone has been in maintenance mode since the Mintlify acquisition on March 3, 2026 (security updates, bug fixes, and new models continue, but no new features), whereas TrustGate is actively developed as a security-first control plane.

The decision usually turns on two axes. The first is the security model: TrustGate treats a first-party Security Engine as the gateway's reason for existing and provides inline enforcement with multi-turn analysis, while Helicone provides operational controls and observability without an inline detection or guardrail layer. The second is roadmap and scope: Helicone is an excellent choice for teams that want the simplest open-source observability-and-routing gateway for LLM applications and are comfortable with its maintenance-mode status, whereas TrustGate is the choice for security-led buyers who need active development, MCP and A2A governance, and a posture companion.

A security-led buyer, or any team whose roadmap depends on new gateway and security capabilities, will likely prefer TrustGate. A team that wants a simple, mature, open-source observability gateway for LLM traffic (and is prepared to self-host and own the maintenance burden) will find Helicone a strong and pleasant tool for exactly that job.

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Key Takeaways

• TrustGate's biggest differentiators are a first-party Security Engine (TrustGuard) with multi-turn analysis, MCP and A2A governance, unified multi-protocol tracing with inline security findings, a companion posture product (TrustLens), and active development.
• Helicone is an open-source LLM observability platform and AI gateway, celebrated for a single-URL integration, a fast Rust proxy, 100+ models, caching, rate limiting, fallbacks, and a polished dashboard.
• Helicone was acquired by Mintlify on March 3, 2026, and is in maintenance mode: security updates, bug fixes, and new models continue, but new feature development has stopped.
• Helicone has no first-party AI detection engine or inline guardrail layer (no prompt-injection, PII, or jailbreak enforcement under one policy engine); its strengths are observability and cost control.
• MCP appears in Helicone only as a data-export server, not tool governance, and A2A is not a gateway feature. TrustGate governs both.
• Both are Apache 2.0 and self-hostable (Helicone via Docker or Helm; hosted service is SOC 2 and GDPR compliant).
• For observability and simplicity, Helicone is excellent; for runtime AI security and agentic governance, TrustGate is purpose-built and actively developed.
• The choice usually reduces to an actively developed, security-first control plane (TrustGate) versus a mature, maintenance-mode observability gateway (Helicone).

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Frequently Asked Questions

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

TrustGate is a security-first, actively developed AI gateway whose Security Engine (TrustGuard) attaches to every Route and which covers LLM, MCP, and A2A traffic with inline security findings. Helicone is an open-source LLM observability platform and AI gateway focused on request analytics, cost tracking, caching, and multi-provider routing, now in maintenance mode after its acquisition by Mintlify.

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; they target different needs. Security-led buyers wanting a first-party enforcement engine, MCP and A2A governance, and active development tend toward TrustGate. Teams wanting a simple, open-source observability and routing gateway for LLM applications tend toward Helicone.

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; Helicone has no equivalent companion layer.

6. Is Helicone still safe to use after the Mintlify acquisition?

The open-source project remains live under Apache 2.0, the proxy still routes traffic to 100+ models, and the hosted service still operates. Helicone announced on March 3, 2026 that it had joined Mintlify and would continue in maintenance mode with security updates, bug fixes, and new models, but no new features. For needs met by what exists today it is fine; for roadmaps depending on new gateway or security features, a migration plan or an actively developed alternative is worth considering.

7. How does Helicone handle runtime security?

Helicone provides operational controls (rate limiting per user, team, or API key, centralized provider-key management, caching, and complete request logging) plus SOC 2 and GDPR compliance and encryption for its hosted service. It does not provide a first-party AI content-detection engine or an inline guardrail layer for prompt-injection, PII, or jailbreak enforcement.

8. What makes Helicone's integration so simple?

Instead of wrapping the LLM client in a new SDK, Helicone asks the application to change a single base URL to the Helicone gateway. From that one change it provides logging, cost tracking, caching, rate limiting, and access to 100+ models through an OpenAI-compatible interface.

9. Does Helicone support MCP or agent-to-agent (A2A) traffic?

Helicone offers an MCP server for exporting and managing your Helicone data, not for governing agents' MCP tool calls, and A2A is not a gateway feature. TrustGate governs MCP tool traffic per Consumer and covers A2A alongside LLM and MCP.

10. Which has better observability?

Both are strong. Helicone offers a mature, low-friction analytics dashboard for requests, sessions, cost, latency, and caching, though its logs are request-centric rather than a deep span tree. TrustGate emphasizes a single unified multi-protocol trace tree with cost, latency, and security findings attributed inline.

11. Is Helicone open source and self-hostable?

Yes. Helicone is Apache 2.0 licensed and can be self-hosted with Docker Compose or a production Helm chart, keeping data under the customer's control. Its hosted service is SOC 2 and GDPR compliant with encryption in transit and at rest.

12. Can Helicone and a security gateway be used together?

Yes, they can be complementary. A team could keep Helicone for its observability and routing while placing a security-first gateway such as TrustGate in the path for runtime enforcement, MCP and A2A governance, and posture coverage, since the two address different primary problems.

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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.