NeuralTrust

What is NeuralTrust?

NeuralTrust is an enterprise platform for governing, securing, and monitoring AI agents and large language models in production. It gives security and platform teams real-time visibility into agent behavior, runtime threat detection, and centralized policy enforcement across LLM deployments. Built for regulated industries like finance and healthcare, NeuralTrust focuses on the gap between deploying AI agents and keeping them safe at scale.

Key Features

• TrustGate (Open-Source AI Gateway): Routes traffic to multiple LLMs through a single endpoint with zero-trust security, semantic caching, and centralized policy controls. Handles 20,000 requests per second at under 1ms response latency.
• TrustTest Red Teaming: Tests LLMs against 150+ attack types including jailbreaks, prompt injections, and hallucination triggers before they reach production.
• TrustLens Observability: Monitors LLM interactions in real time with behavioral analysis and 99% multilingual detection to catch threats that go beyond single-prompt analysis.
• Prompt Guard: Watches agent actions and intent at runtime to block unintended commands from injection attacks like indirect prompt injection (IPI), with under 100ms latency.
• Guardian Agent: Keeps agent behavior within policy-defined limits during execution, adding a runtime safety net as agents take on more autonomous tasks.
• MCP Gateway: Applies granular role-based access controls at the MCP orchestration layer to prevent unauthorized tool use and privilege escalation across 50+ agent deployments.
• MCP Scanner: Continuously checks MCP code for vulnerabilities in the orchestration layer, protecting the integrity of interconnected agent tools.
• Agent Security Suite: Combines MCP Gateway, MCP Scanner, and native SIEM integration to monitor 6,000+ applications and analyze 22M+ interactions. Supports on-prem, SaaS, and hybrid deployment.

Use Cases

• Securing production AI agents in regulated industries: A security team at a financial services company deploys NeuralTrust to enforce policies on customer-facing AI agents, catching prompt injection attempts and blocking unauthorized data access before responses reach end users.
• Red teaming LLMs before launch: A product team runs TrustTest against their new model deployment, scanning for jailbreaks and hallucination vulnerabilities across 150+ documented attack patterns to fix issues before going live.
• Centralizing LLM access and governance: A platform engineering team uses TrustGate to route all LLM traffic through one control point, applying consistent security policies, rate limits, and audit logging across OpenAI, Anthropic, and internal models.

Strengths and Weaknesses

Strengths:

• Covers the full stack from gateway to runtime to observability, so teams do not need to stitch together multiple point solutions for AI security.
• TrustGate is open source, which means teams can self-host, inspect the code, and avoid vendor lock-in on the gateway layer.
• Published performance benchmarks (20,000 req/s, sub-1ms latency) suggest the gateway adds minimal overhead to production traffic.
• The 150+ attack catalog in TrustTest gives concrete coverage numbers rather than vague "AI safety" promises.

Weaknesses:

• Public user reviews are sparse. G2 shows minimal review volume, which makes it harder to verify real-world reliability from independent sources.
• Enterprise pricing is not published. Teams need to contact sales for quotes, which slows down evaluation for smaller organizations.
• Community presence and third-party content are limited compared to more established security tools, so finding help outside official channels can be difficult.
• The platform targets enterprise scale, which may be overkill for teams running fewer than a handful of agents in early-stage pilots.

Pricing

• Free (Open Source): TrustGate is available as an open-source project on GitHub. Teams can self-host the AI gateway with zero-trust security, traffic management, and policy controls at no cost.
• Enterprise: Custom pricing, contact sales. Includes the full Agent Security Suite with TrustTest, TrustLens, Prompt Guard, Guardian Agent, MCP Gateway, MCP Scanner, and SIEM integration. Supports on-prem, SaaS, and hybrid deployment.

FAQ

What types of AI threats does NeuralTrust protect against?

NeuralTrust detects and blocks prompt injections (including indirect prompt injection), jailbreak attempts, data leaks, hallucinations, goal hijacking, and unauthorized tool use. TrustTest covers 150+ documented attack patterns for pre-deployment testing.

Does NeuralTrust support on-premises deployment?

Yes. NeuralTrust supports deployment in a private cloud, your own VPC, or a data center. The open-source TrustGate component can also be fully self-hosted.

Is TrustGate really open source?

Yes. TrustGate is available on GitHub under an open-source license. Teams can inspect the code, contribute, and deploy it independently of NeuralTrust's commercial products.

What performance overhead does NeuralTrust add?

NeuralTrust reports under 1ms response latency for gateway operations and under 100ms for Prompt Guard runtime checks. Published benchmarks show 20,000 requests per second with linear scalability.

Does NeuralTrust enforce zero data retention?

Yes. NeuralTrust states that it enforces zero data retention for AI agents through its architecture and provider-side controls, which matters for teams in regulated industries.

What LLM providers does NeuralTrust work with?

TrustGate centralizes access to hundreds of AI models through a single integration point, including OpenAI, Anthropic, AWS, and GCP-hosted models. It handles unified routing, security, monitoring, and billing across endpoints.