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AI security posture management is decided by one question: does your posture reflect what agents actually do, or only how they are configured? An agent's real risk does not live in its settings. It lives in the calls it makes, the data it touches, and the tools it invokes while it runs. Posture that scores declared configuration tells you how an agent was set up. Posture built on observed behavior tells you what it did. If an agent reached into Notion and pulled a record, you want to know because you saw it happen, not because a permission was checked in a config panel.
TrustLens is NeuralTrust's posture management layer. It identifies every agent in the enterprise and tracks how each one behaves, inside and outside the security perimeter, because it is integrated directly in the interaction path rather than bolted on from the side. Zenity is an agentless AI agent security and governance platform that connects to SaaS platforms through their APIs and reads configuration and platform telemetry. Both are enterprise-ready, so this comparison focuses on what actually separates them for AI-SPM: whether posture is observed or declared, whether the tool is integrated directly in the path or agentless, and how far its view of real agent behavior reaches.
TL;DR
- NeuralTrust posture reflects observed behavior. TrustLens tracks what agents actually do because it is integrated directly in the interaction path. Zenity's posture management evaluates declared configuration and permissions.
- NeuralTrust is integrated directly, not agentless. All agent traffic flows through its gateway and into TrustLens. Zenity connects to SaaS platforms through their APIs and depends on what each platform exposes.
- NeuralTrust sees every agent's real tool calls. Zenity is centered on SaaS-managed platform agents and the telemetry those platforms provide.
- Both bring enterprise readiness, so that is a point of parity, not the deciding factor.
NeuralTrust vs Zenity: AI-SPM at a Glance
| Capability | NeuralTrust | Zenity |
|---|---|---|
| Enterprise readiness | ✅ | ✅ |
| Native AI gateway integration | ✅ | ❌ |
| Flexible deployment (private, cloud) | ✅ | ❌ |
| Directly integrated in the interaction path | ✅ | ❌ |
| Observed behavior, not declared configuration | ✅ | ❌ |
| Coverage of every agent's real tool calls | ✅ | ❌ |
NeuralTrust vs. Zenity: 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, inside and outside the security perimeter, building posture from what agents actually do rather than from how they were set up.
TrustLens sees behavior because it is integrated directly in the interaction path. Agent traffic flows through TrustGate, NeuralTrust's AI gateway and the single point through which every LLM, MCP, and tool call passes, and that traffic feeds TrustLens with trace-level detail on every execution. So when an agent invokes a tool, reads data, or reaches an external service, TrustLens records the actual inputs, outputs, and system calls, maps them to frameworks like OWASP, MITRE, and ISO, and makes the whole history searchable. Posture here is grounded in observed behavior: what happened, seen firsthand, not inferred from a configuration.
And because TrustLens sits on the same platform as NeuralTrust's runtime security enforcement, posture is not just a diagnosis. What TrustLens observes can be acted on in the path, so the gap between seeing a risky behavior and stopping it closes. It runs in your private environment or in the cloud, and it carries the enterprise readiness that a security platform in production demands.
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What is Zenity?
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Zenity is an agentless AI agent security and governance platform. It is organized into three modules: Zenity Observe for discovery and telemetry, Zenity Govern for AI security posture management, and Zenity Defend for detection and response. It connects to SaaS platforms through their APIs, covering agents such as Microsoft 365 Copilot, Copilot Studio, Salesforce Agentforce, and ChatGPT Enterprise, along with cloud model services.
Because it is agentless, Zenity assembles its view from what those platforms expose through their connectors and from the configuration of each agent. Its posture management module evaluates how agents are configured, reviewing permissions, integrations, memory, and tool access, and enforces policy against declared settings before deployment. That model discovers agents and governs configuration across the SaaS platforms it connects to, but its picture of any given agent is bounded by the telemetry each platform provides and by the configuration it can read, rather than by direct observation of the agent's traffic. It holds enterprise certifications including SOC 2 Type II and ISO 27001, so it meets the enterprise bar on that front.
Native AI Gateway Integration: Observing at the Enforcement Point vs Connecting Through Platform APIs
Posture is only as good as the vantage point it is built from. Watching agents from the single point their traffic flows through gives you the real interaction. Connecting to platforms through their APIs gives you what those platforms decide to report.
TrustLens is built on top of TrustGate, NeuralTrust's AI gateway, which brokers every LLM, MCP, and tool call. That gateway is the chokepoint through which agent traffic passes, and it feeds TrustLens the actual requests and responses. Posture, discovery, and behavior tracking all draw from that live vantage point, so the picture is the traffic itself, not a secondhand account of it.
Zenity has no gateway. It is agentless, connecting to each SaaS platform through that platform's APIs and reading the telemetry and configuration those APIs return. That means its view of an agent is mediated by the platform: it sees what Microsoft, Salesforce, or another vendor chooses to expose, at the granularity that vendor provides, and nothing that flows outside those connectors. A gateway that carries the traffic sees the interaction directly, where a connector that queries a platform sees a report of it. TrustLens sits at the gateway.
Flexible Deployment: Private and Cloud vs SaaS-Delivered
Where a posture platform runs decides which environments it can cover and where your agent data goes. Some organizations need posture and observability running inside their own environment, not delivered 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.
Zenity is a SaaS-delivered, agentless platform. Its model is to connect to your SaaS platforms from Zenity's service and pull telemetry back, which ties its coverage to that SaaS delivery rather than running as posture inside your own environment. For organizations that want their agent observability and posture deployed privately, a SaaS-only platform does not offer that option. TrustLens does.
Directly Integrated in the Interaction Path: First-Party vs Agentless Connectors
The difference between watching an agent and querying a platform about it is the difference between firsthand and secondhand. Posture built firsthand does not have a platform standing between it and the truth.
TrustLens is integrated directly in the interaction path. The traffic runs through NeuralTrust's own gateway and into TrustLens, so the observation is first-party: the actual call, the actual payload, the actual response, captured as it happens. Nothing depends on a third-party platform choosing to surface it, and coverage does not stop at the edge of a vendor's connector.
Zenity is agentless by design, and its integration is through the APIs of the platforms it connects to. That is convenient to stand up, but it makes every observation dependent on the connector and the platform behind it. If a platform does not expose a detail, or exposes it late or coarsely, Zenity's view inherits that limit. Agentless connectors give you the platform's account of the agent, not the agent's actual traffic. TrustLens is in the path, so it has the traffic.
Observed Behavior, Not Declared Configuration: What Agents Do vs How They Are Configured
This is the heart of AI-SPM. A configuration says what an agent is allowed to do. Behavior says what it did. The two diverge exactly where risk lives, in the tool an agent invoked that it never should have, the data it moved, the action it took that no permission would have predicted.
TrustLens builds posture from observed behavior. Because it sits in the path, it records the real interaction and reports posture on what agents actually did: which tools they called, which data they touched, which external services they reached. When an agent accesses a resource, TrustLens knows because it saw the call, not because a setting implied it was possible. Posture that reflects behavior catches the divergence between what an agent may do and what it does.
Zenity's posture management evaluates declared configuration. Its AI-SPM module reviews how agents are configured, their permissions, integrations, memory, and tool access, and validates that posture against policy. That is assessment of the declared state: what the agent is set up to do. Zenity does collect telemetry through its Observe module, but its posture is anchored in configuration read through platform connectors, so it describes how an agent is arranged rather than what it did in the moment. Declared configuration is a plan. Observed behavior is the record. TrustLens reports the record.
Coverage of Every Agent's Real Tool Calls: The Actual Execution vs Platform Telemetry
An agent's risk shows up in its tool calls, the invocations where it reaches data and takes action. Posture that covers those calls for every agent sees the real attack surface. Posture bounded to a set of SaaS platforms sees only part of it.
TrustLens covers every agent's real tool calls because every LLM, MCP, and tool call flows through the gateway it observes. Whether an agent is a packaged SaaS copilot or a custom build wired to internal tools, the actual execution passes through the path TrustLens watches, so its tool calls, inputs, and outputs are captured the same way for all of them.
Zenity is centered on SaaS-managed platform agents and the telemetry those platforms provide, such as Microsoft 365 Copilot, Copilot Studio, Salesforce Agentforce, and ChatGPT Enterprise. Its coverage of any agent's real tool-call execution is bounded by what those platform connectors expose, so agents and interactions outside that connector set, or details a platform does not surface, fall outside its view. Covering the SaaS platforms an agent runs on is not the same as covering the actual tool calls every agent makes. TrustLens covers the calls.
Final Verdict
AI-SPM comes down to whether posture reflects observed behavior or declared configuration, and that depends on how the tool is integrated. A platform in the interaction path reports what agents did. An agentless platform that connects through SaaS APIs reports what those platforms expose and how agents are configured.
TrustLens is integrated directly in the path. It builds posture from observed behavior, tracks how every agent actually acts because all agent traffic flows through NeuralTrust's gateway and into TrustLens, covers every agent's real tool calls rather than a set of SaaS platforms, and runs in your private environment or the cloud. And because it shares a platform with NeuralTrust's runtime security enforcement, what it observes can be acted on in the path, so posture leads to prevention rather than to a report. It is enterprise-ready, as production security has to be.
Zenity is agentless and connects to SaaS platforms through their APIs. It discovers agents and governs their configuration across those platforms, with posture anchored in declared settings and a view mediated by each platform's connector and telemetry. It is enterprise-ready and it covers the SaaS agents it connects to, but its posture describes how agents are configured more than what they actually do, and its coverage stops at the edge of the platforms it queries.
Both clear the enterprise bar, so that is not the deciding factor. The decision is whether you want posture built on what agents actually do, from a platform integrated directly in the path, or posture built on declared configuration, from an agentless connector to your SaaS platforms. If you want to know what your agents did because you saw it, NeuralTrust is built for exactly that.
Frequently Asked Questions about NeuralTrust vs. Zenity
1. What is the main difference between NeuralTrust and Zenity for AI-SPM?
NeuralTrust TrustLens is integrated directly in the interaction path and builds posture from observed behavior, what agents actually do. Zenity is agentless, connecting to SaaS platforms through their APIs and building posture from declared configuration and platform telemetry. One reports the record of what happened, the other describes how agents are configured.
2. Does Zenity observe actual agent behavior?
Zenity collects telemetry through its Observe module, but as an agentless platform its view is mediated by the SaaS platform connectors it relies on, and its posture management is anchored in declared configuration. NeuralTrust sits in the interaction path through its gateway, so it observes the actual calls, payloads, and responses firsthand rather than through what a platform chooses to expose.
3. Why does being integrated directly in the path matter?
Because posture built in the path is firsthand. TrustLens sees the real interaction as it happens and does not depend on a third-party platform surfacing it. An agentless connector inherits the limits of the platform behind it, so if a detail is not exposed, or is exposed coarsely, the posture picture inherits that gap. Direct integration removes the middleman between your posture and the truth.
4. Can both products be deployed privately?
NeuralTrust TrustLens runs in your private environment or in the cloud, so posture and observability can live inside your perimeter. Zenity is a SaaS-delivered, agentless platform, so it operates as an outside service that connects to your SaaS platforms rather than running privately inside your own environment.
5. Are both platforms enterprise-ready?
Yes. Both NeuralTrust and Zenity meet the enterprise bar, with certifications and controls expected of production security platforms, so enterprise readiness is a point of parity. The meaningful differences are observed versus declared posture, direct in-path integration versus agentless connectors, and coverage of every agent's real tool calls versus the SaaS platforms a connector reaches.
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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