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AI security posture management is decided by where you watch agents from and how deep that view goes. An agent's real risk lives in the calls it makes: the tool it invokes, the data it moves, the action it takes. A platform that watches from the network sees traffic crossing the wire. A platform integrated at the interaction layer sees the actual structured call, the agent behind it, and the tool it reached. Same event, two very different levels of truth, and posture is only as good as the level it is built from.
TrustLens is NeuralTrust's posture management and observability layer. It identifies every agent in the enterprise and tracks how each one behaves, because it is integrated directly at the interaction layer, where every LLM, MCP, and tool call flows through NeuralTrust's gateway and into TrustLens. WitnessAI approaches AI from the network. It is a network-level governance platform, delivered as a single-tenant cloud service, that intercepts AI traffic to give visibility and control primarily over how employees use AI. Both observe real activity and both are enterprise-ready, so this comparison focuses on what actually separates them for AI-SPM: the layer the view is built from, how deep it reaches into real tool calls, and where the platform runs.
TL;DR
- NeuralTrust observes at the interaction layer. TrustLens sees the actual structured LLM, MCP, and tool calls because it sits where that traffic flows. WitnessAI intercepts at the network layer, built primarily around employee AI usage.
- NeuralTrust is built on a native AI gateway. Every call is brokered through it and feeds posture. WitnessAI has no gateway and uses network interception with prompt routing.
- NeuralTrust runs in your private environment or the cloud. WitnessAI is delivered as a single-tenant cloud service.
- NeuralTrust covers every agent's real tool-call execution. WitnessAI's agent view centers on network-level visibility of MCP connections. Both are enterprise-ready, so that is parity.
NeuralTrust vs WitnessAI: AI-SPM at a Glance
| Capability | NeuralTrust | WitnessAI |
|---|---|---|
| Enterprise readiness | ✅ | ✅ |
| Native AI gateway integration | ✅ | ❌ |
| Flexible deployment (private, cloud) | ✅ | ❌ |
| Directly integrated at the interaction layer | ✅ | ❌ |
| Interaction-level view of real tool calls | ✅ | ❌ |
| Coverage of every agent's real tool-call execution | ✅ | ❌ |
NeuralTrust vs. WitnessAI: Platform Overview
What is NeuralTrust TrustLens?
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TrustLens is NeuralTrust's AI posture management and observability layer. It identifies every agent across the enterprise and tracks how each one behaves, building posture from the actual interactions rather than from network traffic alone.
TrustLens gets that depth because it is integrated directly at the interaction layer. Agent traffic flows through TrustGate, NeuralTrust's AI gateway and the single point every LLM, MCP, and tool call passes through, and that call feeds TrustLens with structured, trace-level detail. So TrustLens records the real invocation: the tool that was called, the inputs and outputs, the agent identity behind it, and the protocol it used, then maps it to frameworks like OWASP, MITRE, and ISO and makes the whole history searchable. Posture is grounded in the actual call, at the semantic level, not inferred from packets on the wire.
And because TrustLens sits on the same platform as NeuralTrust's runtime security enforcement, what it observes can be acted on in the same path, so posture leads to prevention rather than to a report. It runs in your private environment or in the cloud, and it carries the enterprise readiness a production security platform demands.
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What is WitnessAI?
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WitnessAI is a network-level AI security and governance platform, delivered as an isolated single-tenant cloud service that intercepts AI traffic without a device agent. It is organized into three modules: Observe for visibility, Control for policy and prompt routing, and Protect for runtime defense. It connects through proxy chaining with existing security infrastructure, API integration, or an endpoint option for off-network use.
Its center of gravity is governing how employees use AI. Observe surfaces shadow AI and catalogs the AI applications, agents, and MCP servers in use, Control applies intent-based policy and redaction and routes prompts across models, and Protect adds runtime defense against prompt injection and jailbreaks. For agents, WitnessAI provides network-level visibility into which agents exist and which MCP servers they connect to, controls access to approved MCP servers, and attributes agent actions to a human identity. It observes real activity, and it does so from the network, which means its view of any given agent is the traffic it intercepts rather than the structured call captured at the point of execution. It holds SOC 2 and serves enterprise customers, so it meets the enterprise bar.
Native AI Gateway Integration: Brokering Every Call vs Network Interception
Posture is built from a vantage point, and the vantage point decides the depth. A gateway that brokers every call sees each one as a structured event. Network interception sees the traffic that carries it.
TrustLens is built on TrustGate, NeuralTrust's AI gateway, which brokers every LLM, MCP, and tool call. Because the gateway is the point the traffic passes through, it hands TrustLens the call itself, structured and complete, and posture, discovery, and behavior tracking all draw from that. The gateway is both the enforcement point and the source of truth for posture.
WitnessAI has no gateway. It intercepts AI traffic at the network level and adds prompt routing inside its Control module, but routing prompts is not the same as brokering every LLM, MCP, and tool call through a gateway that understands each one as a structured event. Without that gateway, posture is assembled from intercepted traffic rather than from calls brokered at the point of execution. TrustLens has the gateway, so it has the call.
Flexible Deployment: Private and Cloud vs Single-Tenant Cloud Service
Where a posture platform runs decides which environments it can cover and where your agent data lives. Some organizations need posture and observability running inside their own environment, not only as an outside service.
TrustLens runs in your private environment or in the cloud, so posture and behavior tracking can live inside your perimeter, with agent traffic and its telemetry staying where you need them.
WitnessAI is delivered as an isolated single-tenant cloud service. It offers customer-managed keys and data sovereignty options, but the platform itself runs as a cloud service that intercepts your traffic, rather than as software deployed inside your own environment. For organizations that want their agent posture and observability running privately, in their own infrastructure, a single-tenant cloud service is not the same as a private deployment. TrustLens gives you the private option.
Directly Integrated at the Interaction Layer: Application Path vs Network Path
The layer a platform integrates at sets a ceiling on what it can ever see. Sitting in the application path, on the calls themselves, is different from sitting on the network the calls travel across.
TrustLens is integrated directly at the interaction layer, on the LLM, MCP, and tool-call path itself. Its view is the call as the application makes it: the structured request and response, the agent identity, the tool and protocol in use. That is firsthand at the semantic level, and it does not depend on reconstructing meaning from network traffic.
WitnessAI integrates at the network layer, intercepting AI traffic through proxy chaining, API integration, or its off-network endpoint option. That is effective for governing employee AI usage across the network, but it means the platform reasons about agents from intercepted traffic rather than from the call captured at the point of execution. Watching the network the traffic crosses is a different layer than sitting on the interaction itself. TrustLens sits on the interaction.
Interaction-Level View of Real Tool Calls: Structured Calls vs Network Traffic
For AI-SPM, the tool call is the unit that matters. A posture that resolves down to the individual structured call, with its inputs, outputs, and the identity behind it, describes real risk. A posture built from network traffic describes what crossed the wire.
TrustLens sees real tool calls as structured events. Because the call is brokered through the gateway, TrustLens captures exactly which tool was invoked, with what inputs, returning what outputs, from which agent identity, and records it as a first-class object it can search, classify, and map to frameworks. The detail is the call, not a trace of it.
WitnessAI builds its view from intercepted network traffic. It sees AI interactions and MCP connections as they cross the network and applies policy to them, which is valuable for usage governance, but the granularity is bounded by what the network exposes rather than by the structured call at the point of execution. Network traffic tells you an agent talked to a server. The structured call tells you exactly what it asked the tool to do. TrustLens reports the structured call.
Coverage of Every Agent's Real Tool-Call Execution: Every Agent vs MCP Connection Visibility
An agent's risk shows up in the tool-call execution, the moment it reaches data and takes action. Posture that covers that execution for every agent sees the real surface. Posture that maps which servers an agent connects to sees the edges of it.
TrustLens covers every agent's real tool-call execution because every LLM, MCP, and tool call flows through the gateway it observes. Whether an agent is a packaged assistant or a custom internal build, the actual execution passes through the path TrustLens watches, so its calls, inputs, and outputs are captured the same way for all of them.
WitnessAI's agent coverage centers on network-level visibility of which agents exist and which MCP servers they connect to, along with control over approved MCP servers and attribution of agent actions to a human identity. That governs the connections an agent makes and ties them to a person, which is useful, but visibility into the MCP servers an agent reaches is not the same as capturing the real tool-call execution itself. Knowing an agent connected to a server is not knowing what it did through it. TrustLens captures what it did.
Final Verdict
AI-SPM comes down to the layer your posture is built from. A platform integrated at the interaction layer reports the actual structured calls agents make. A network-level platform reports the traffic those calls generate, governed well for employee usage but bounded by what the network exposes.
TrustLens is integrated directly at the interaction layer. It is built on NeuralTrust's AI gateway, so every LLM, MCP, and tool call is brokered through it and captured as a structured event, posture reflects the real tool-call execution of every agent, and because it shares a platform with runtime security enforcement, what it observes can be stopped in the same path. It runs in your private environment or the cloud, and it is enterprise-ready.
WitnessAI is a network-level governance platform delivered as a single-tenant cloud service, built primarily around employee AI usage. It observes real activity, applies intent-based policy, and adds runtime defense, and it is enterprise-ready with its own security controls. But it has no gateway, its view is intercepted network traffic rather than the structured call at the point of execution, its agent coverage centers on MCP connection visibility, and it runs as a cloud service rather than inside your own environment.
Both observe real activity, both bring runtime security controls, and both clear the enterprise bar, so none of those is the deciding factor. The decision is whether you want posture built from the actual structured calls agents make, at the interaction layer, running in your own environment, or posture built from intercepted network traffic, delivered as a cloud service and centered on employee usage. If you want posture that resolves to what every agent actually did, NeuralTrust is built for exactly that.
Frequently Asked Questions about NeuralTrust vs. WitnessAI
1. What is the main difference between NeuralTrust and WitnessAI for AI-SPM?
NeuralTrust TrustLens is integrated directly at the interaction layer, built on an AI gateway that brokers every LLM, MCP, and tool call, so posture reflects the actual structured calls agents make. WitnessAI is a network-level governance platform, delivered as a single-tenant cloud service, that intercepts AI traffic and is built primarily around employee AI usage. One resolves to the structured call, the other to network traffic.
2. Does WitnessAI observe real agent behavior?
Yes, WitnessAI observes real activity, but it does so at the network layer through traffic interception, and its agent coverage centers on which MCP servers an agent connects to. NeuralTrust observes at the interaction layer, capturing the structured tool call itself, with its inputs, outputs, and agent identity, because every call is brokered through its gateway.
3. Does WitnessAI have an AI gateway?
No. WitnessAI intercepts AI traffic at the network level and includes prompt routing in its Control module, but it does not broker every LLM, MCP, and tool call through a gateway. NeuralTrust is built on TrustGate, its AI gateway, which is both the enforcement point and the source of truth for posture.
4. Can both products run in a private environment?
NeuralTrust TrustLens runs in your private environment or in the cloud, so posture and observability can live inside your perimeter. WitnessAI is delivered as an isolated single-tenant cloud service with customer-managed keys, so it operates as a cloud service that intercepts your traffic rather than as software deployed inside your own environment.
5. Are both platforms enterprise-ready and do both include security controls?
Yes. Both NeuralTrust and WitnessAI are enterprise-ready and both include runtime security controls, so those are points of parity. The meaningful differences for AI-SPM are the layer posture is built from, interaction versus network, whether the platform is built on an AI gateway, coverage of every agent's real tool-call execution, and whether it can run in your own private environment.
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 AI Gateways and Guardian Agents, and the KuppingerCole 2025 Leadership Compass for Generative AI Defense. Headquartered in Barcelona with ISO 27001 certification.
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