Salt Security vs. Zenity
Zenity monitors agent behavior.
Salt secures the APIs where behavior becomes damage.
Zenity is a strong AI agent governance platform — purpose-built for observing and governing agent activity across SaaS and endpoint environments, especially the Microsoft stack. What it does not cover is the action layer: the APIs, MCP servers, and downstream services where agent behavior translates into enterprise risk. Salt Security was built for exactly that layer.
AI Observability and LLM Monitoring
Discovery, posture, behavioral detection
Full API Fabric Coverage
All APIs regardless of platform or framework
Agentic Security Graph
LLM, MCP, API, identity correlation
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What each platform was built to do
Agent governance and agentic security
protect different surfaces
Salt Security: purpose-built agentic security
The full API fabric — every platform, every agent framework
Salt Security covers the action layer below and beyond what Zenity monitors: every API, MCP server, and downstream service that agents interact with — regardless of whether the agent runs in Microsoft, a custom LangChain workflow, Databricks, or any other framework. The Agentic Security Graph is platform-agnostic by design, built on eight years of API security research.
- Full API fabric coverage — every platform, every framework, every agent
- Agentic Security Graph across LLM, MCP, API, and identity layers
- Downstream enterprise API and business logic protection
- East-west and internal API coverage with no device agent required
- Identity-aware multi-step sequence correlation
- Salt Code governance in repositories before deployment
- Runtime-to-code remediation loop — detection feeds fixes
Zenity: AI Agent Governance Platform
Step-level agent monitoring across SaaS and endpoints
Founded by Microsoft cloud security veterans and backed by Microsoft's M12, Zenity delivers deep coverage of agent activity within the Microsoft ecosystem — M365 Copilot, Azure AI Foundry, and enterprise SaaS platforms. It monitors agents at the step level, correlates incidents across identity and posture signals, and enforces governance policies across supported platforms.
- Deep Microsoft platform coverage — Copilot, Azure AI, Teams agents
- Step-level agent behavior analysis and incident correlation
- Agentic browser coverage via device agent
- Coverage limited to supported platforms — no LangChain, Databricks, or custom agent frameworks
- No coverage of downstream enterprise APIs and business logic
- Device agent required for endpoint visibility
- No Agentic Security Graph — no cross-fabric LLM, MCP, API correlation
Head-to-head
The agentic capabilities
agent monitoring platforms don’t cover
Zenity tells you what your agents intended. Salt secures what they actually did to your API fabric. These are the capabilities that require action-layer coverage, not step-level behavioral analysis.
| Feature | Description |  |  |
|---|---|---|---|
| Unified Agentic Discovery | Discovers APIs, MCP servers, and AI-driven assets across external exposure, cloud, code repositories, and runtime. |  |  |
| Agentic Security Graph | Correlates LLMs, MCP servers, APIs, identities, and sensitive data in one action-layer context. | | |
| Salt Code Governance | Governs API and MCP creation in repositories, pull requests, and developer workflows before risky logic reaches production. | | |
| Runtime-to-Code Remediation | Feeds runtime findings back into DevOps workflows and AI coding assistants to fix root causes. | | |
| Agent-Aware Sequence Correlation | Tracks unique agentic identities and multi-step intent across sessions, tools, and services. | | |
| Behavioral Action-Layer Protection | Detects machine-speed business-logic abuse beyond signatures, schemas, or prompt filters. | | |
| Internal & East-West Coverage | Protects internal APIs and downstream service interactions that edge-only and model-only tools miss. | | |
| Action-Layer Data Security | Maps sensitive data in motion across APIs, MCP servers, and agent actions. | | |
| Full API Fabric Coverage | Secures traditional internal, external, and third-party APIs alongside agents, MCP servers, and AI assets. | | |
| Platform-Agnostic Agentic Coverage | Covers every agent framework — LangChain, CrewAI, Databricks, custom-built agents, and more — without requiring the agent to run within a natively supported SaaS platform. | | |
| No Device Agent Required | Delivers full agentic security coverage without deploying a device agent to every endpoint — fully out-of-band, zero dependency on endpoint instrumentation for API fabric visibility. | | |
Why it matters
Knowing what an agent intended
is not the same as securing what it touched
Zenity’s step-level monitoring stops at the SaaS boundary. Agents don't.
Zenity’s strength is observing how agents behave inside the platforms it natively supports — Microsoft 365, Salesforce, ServiceNow, ChatGPT Enterprise. It monitors what agents see, decide, and do at each step, and correlates those signals into incident narratives. That is genuinely valuable governance.
The gap is what happens when agent actions trigger downstream API calls, access internal microservices, or operate through agent frameworks Zenity does not natively cover. Zenity's platform is explicitly agent-centric — Salt's is API-fabric-centric. For enterprises where agents interact with custom-built internal APIs and services, Salt is covering the surface that Zenity's architecture does not reach.
What Salt covers that Zenity cannot reach
- Business logic abuse in enterprise APIs called by agents running outside Zenity's supported platform list
- Internal east-west API traffic triggered by agent actions after initial SaaS interaction
- Shadow APIs and rogue MCP servers created outside any SaaS platform — entirely outside Zenity's discovery model
- Custom agent frameworks — LangChain, CrewAI, Databricks agents — with no Zenity platform integration
- Risky API and MCP logic in developer repositories before any agent platform has been configured to monitor it
Salt code
Security before any agent platform is configured to monitor it
Zenity’s governance model activates once agents are deployed and producing behavior signals. Salt Code governs API and MCP creation at the repository level — scanning pull requests for risky integrations and agentic exposures before they ship, regardless of which platform will eventually run the agent. Runtime findings feed back into developer workflows automatically, so the underlying vulnerabilities are fixed at the source.
3
layers covered:
LLM, MCP, API
0
device agents or
platform connectors required
11
capabilities beyond
Zenity’s agent model
8
years of production
API security research
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