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License: Apache-2.0 Any use incl. commercial
Local-run terms: Self-host the binary or build from source under Apache-2.0; commercial support available for enterprise features.

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NeuralTrust TrustGate

PaidOpen SourceAPISelf-Hosted

Pricing

Model
Subscription

Summary

Autonomous agents making decisions across a dozen services, with no central record of what they accessed, who they called, or what they returned — that's the gap TrustGate exists to close.

NeuralTrust TrustGate sits between your agents and the models, tools, and services they reach, enforcing policy at the interaction level rather than bolting controls on after the fact. The vendor states the gateway handles real-time enforcement at sub-100ms latency and claims behavioral, contextual, and multilingual detection across 22 million-plus AI interactions analyzed. Self-hosted deployment via on-prem or VPC keeps data inside your perimeter — a hard requirement in regulated industries where data leaving the environment ends the conversation. The open-source core is Apache-2.0 licensed, which means your security team can audit what is actually running. Enterprise features, SIEM integration, and dedicated support are paid-only.

Bottom line: TrustGate earns its place when you need auditable, policy-enforced control over agents running across a regulated environment — but if your agents are homogeneous and your threat model is shallow, you are buying governance infrastructure you will spend a sprint configuring before you see a single blocked request.

Community Performance Report Card

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Best For: Enterprise AI security teams, Regulated industries requiring data sovereignty, Organizations running autonomous agents at scale, Self-hosted LLM gateway deployments
  • Split-plane architecture separates control from data, so regulated teams can enforce policy on-prem while agents connect to external models — which means data sovereignty requirements do not force a choice between compliance and capability.
  • Apache-2.0 open-source core, so your security team can audit the inspection logic rather than trusting a vendor's attestation — critical when the gateway itself sits in a sensitive data path.
  • Real-time behavioral and contextual inspection with sub-100ms latency claimed by the vendor, so enforcement does not become the bottleneck that teams route around to hit throughput targets.
  • Centralized agent inventory that surfaces every deployed agent, connected tool, and execution workflow, so blind spots that traditional controls miss — agents operating outside the core codebase, third-party SaaS agents — are visible and governable.
  • Native SIEM integration, so agent security events appear in the same alert pipeline security operations already monitors rather than requiring a separate console to watch.
  • The platform's value is proportional to agent sprawl — a team running one or two agents in a controlled environment will spend significant setup time on discovery, policy configuration, and SIEM wiring before the governance layer returns anything actionable. The overhead makes sense at scale; it does not make sense for a contained pilot.
  • Enterprise features, dedicated support, and the full attack catalogue are paid-only, meaning the open-source deployment gets you the gateway but leaves the red teaming catalog and posture management depth behind a commercial gate. Teams that need adversarial test coverage as part of their security program — not just runtime enforcement — face a budget decision before they can use the full stack.
  • Organizations whose primary threat model is prompt injection on a single public-facing model, rather than cross-agent lateral movement or data leakage across tool chains, will find more targeted and lower-friction solutions in standalone guardrail libraries; at that scope, TrustGate's agent-inventory and posture-management infrastructure goes largely unused, and teams moving fast on a contained product typically switch to a thinner layer rather than right-size the configuration.

About

Platforms
On-prem, VPC, SaaS, hybrid
API Available
Yes
Self-Hosted
Yes
Last Updated
2026-08-14T02:58:24.641Z

Best For

Who it's for

  • Enterprise AI security teams
  • Regulated industries requiring data sovereignty
  • Organizations running autonomous agents at scale
  • Self-hosted LLM gateway deployments

What it does well

  • Real-time protection of AI agent interactions
  • Centralized governance of deployed agents and tools
  • Adversarial testing and red teaming of models
  • Policy enforcement for third-party AI infrastructure

Integrations

OpenAIAnthropicAzure OpenAISIEMagentic platforms
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Frequently Asked Questions

Is NeuralTrust TrustGate free?
NeuralTrust TrustGate is a paid tool. No permanent free tier is offered.
Is NeuralTrust TrustGate open source?
Yes. NeuralTrust TrustGate is open source.
Does NeuralTrust TrustGate have an API?
Yes. NeuralTrust TrustGate exposes a developer API. See the official documentation at https://neuraltrust.ai for details.
Can I self-host NeuralTrust TrustGate?
Yes. NeuralTrust TrustGate supports self-hosting on your own infrastructure.
What platforms does NeuralTrust TrustGate support?
NeuralTrust TrustGate is available on: On-prem, VPC, SaaS, hybrid.

The visibility gap in agent sprawl

Autonomous agents making decisions across a dozen services, with no central record of what they accessed, who they called, or what they returned — that’s the gap TrustGate exists to close.

NeuralTrust TrustGate sits between your agents and the models, tools, and services they reach, enforcing policy at the interaction level. The vendor states the gateway handles real-time enforcement at sub-100ms latency and claims behavioral, contextual, and multilingual detection across 22 million-plus AI interactions analyzed. Self-hosted deployment via on-prem or VPC keeps data inside your perimeter. The open-source core is Apache-2.0 licensed.

Deployment and controls

Platforms include on-prem, VPC, SaaS, and hybrid. Integrations cover OpenAI, Anthropic, Azure OpenAI, SIEM, and agentic platforms. An API is available. Pricing follows a subscription model.

Who it is for / who should skip it

Best for enterprise AI security teams, regulated industries requiring data sovereignty, organizations running autonomous agents at scale, and self-hosted LLM gateway deployments. Teams gain a split-plane architecture that separates control from data and can audit the inspection logic. Skip it for a contained pilot with one or two agents, where setup time on discovery, policy configuration, and SIEM wiring outweighs returns. Enterprise features and the full attack catalogue sit behind paid access.