NeuralTrust
TrustGate by NeuralTrust is an open-source AI gateway built to secure and govern enterprise usage of large language models (LLMs) and AI agents at scale. It acts as a centralized control point that sits in front of all AI traffic, enabling organizations to enforce security policies, control access, and gain full observability over every request and response. The gateway supports model routing across major providers like OpenAI, Anthropic, Azure OpenAI, and self-hosted models, allowing teams to switch models without changing application code. It also implements the Model Context Protocol (MCP) to give agents scoped access to internal tools and APIs, and the Agent-to-Agent (A2A) protocol for secure delegation and traceability between agents. Inline security features include real-time prompt injection and jailbreak detection with 99% multilingual accuracy, PII redaction, and semantic caching to reduce latency and cost. TrustGate is designed for production environments, delivering less than 100ms added latency at p95 with security checks enabled, and sustaining over 20,000 requests per second per node. All interactions are logged, providing audit trails for compliance and governance. TrustGate is part of NeuralTrust's broader AI security platform, which includes agent posture management and red teaming tools. The company has raised $20 million in funding and is used by enterprises in highly regulated industries such as banking and aviation. The open-source core is available on GitHub, making it suitable for self-hosted deployments where data must remain on-premises, while a managed cloud offering is also available for organizations preferring a SaaS model.
- Category
- Open Source AI Models
- Pricing
- Unknown
Problem solved
As enterprises deploy dozens of AI agents that interact with multiple models and internal tools, they face fragmented security, lack of visibility, and inconsistent policy enforcement. Without a gateway, each agent or developer must implement their own security controls, leading to gaps in prompt injection defense, data leakage risks, and ungoverned tool access. TrustGate centralizes all AI traffic, applying uniform authentication, authorization, content filtering, and logging, thus mitigating threats and ensuring compliance without slowing down innovation.
Use cases
- Securely routing LLM API calls across multiple providers with a single integration point
- Enforcing least-privilege access for AI agents to internal tools and data via MCP
- Enabling agent-to-agent collaboration with full audit trails for every delegation
- Redacting PII from prompts and responses to comply with data privacy regulations
- Detecting and blocking prompt injections and jailbreak attempts in real time
- Caching frequent LLM responses to reduce latency and API costs
- Logging all AI interactions for forensic analysis and regulatory reporting
Audience
- Developers
- ML Engineers
- Enterprise
- Data Scientists
Pros
- Open-source core with permissive license
- Inline security inspections add minimal latency (<100ms p95)
- Supports multiple model providers and switching without code changes
- Implements MCP and A2A protocols for tool access and agent orchestration
- High throughput (20k+ req/s/node) suitable for enterprise scale
Cons
- Requires infrastructure expertise to deploy and scale in self-hosted mode
- Adds a critical component that must be highly available; could become a bottleneck if not properly sized
- Open-source version may lag behind managed offering in features and support
- Pricing for enterprise features or managed service is not transparent
- Relatively new project with evolving documentation and community
Official website: https://neuraltrust.ai/ai-gateway
Canonical LambdaBase page: https://www.lambdabase.com/tools/neuraltrust