Is Ent or Zenity better for AI endpoint control?

Neither is scored on this site. Ent describes 2 of four product control types and Zenity 1 on the pages we read, and they differ on 8 recorded facts. Which fits depends on the AI tools people use, your devices, where the work happens and whether you block or guide; the finder checks those.

Which of the two decides on a tool call before it runs?

Ent: Partly. Zenity: Matches. Warn or ask: Ent Matches, Zenity Partly.

Do Ent or Zenity publish prices?

Ent: Not published (demo request). Zenity: Not published.

HEAD-TO-HEAD · FACTS ONLY

Ent vs Zenity: AI endpoint control facts side by side

Short answer

Ent describes 2 of the four product control types on the pages we read and Zenity describes 1; they differ on on-device control, browser extension and AI or MCP gateway. On decisions, Ent describes some control over tool calls and Zenity decides on a tool call before it runs. We do not score either; the right choice depends on the AI tools people use, your devices, your current stack and whether you block or guide.

By The Device Desk · Endpoint AI Finder · Published 2026-10-11

Desk research from public vendor pages read on 27 September and 11 October 2026. Profiles follow our published method; we did not run the products.

Vendor pages read September and October 2026 · updated 2026-10-13

Where do their controls sit?

Filled or hatched marker: Ent
Dashed teal ring: Zenity, described

DEV Filled marker: described on the product pages we read
DEV Hatched marker: partly described (another component, a narrower scope, or method not detailed)
DEV Dashed marker: not in our sources (it may exist; we did not find it)

The map shows where each product's own pages describe a control, or where your answers point. It is not a measure of how well a product works.

What are the facts, side by side?

Ent and Zenity, from each product's own pages. Differs is computed from recorded statuses, not wording.
Fact	Ent	Zenity
Owner	None	None
Positioning	An intent-aware AI endpoint: one programmable policy for people and AI agents, with interventions from a soft nudge to a hard block, an on-device small language model that classifies sensitive data, and investigation timelines written in plain language. Use cases: insider risk, last-mile threats such as ClickFix, AI usage control and data security.	An AI agent security platform covering AI observability, posture management, exposure management, runtime boundaries, agentic identity, MCP security and AI detection and response, with a long list of SaaS and cloud agent integrations.
How it reaches devices	A single lightweight agent across Windows, macOS, Linux and modern browsers, run as SaaS or self-hosted in your own cloud; rollout through MDM is not stated. Source: Ent press: intent-aware prevention for AI agents, 30 July 2026 · Read 13 Oct 2026	Native agent hooks and the Zenity MCP gateway for coding agents; how it reaches endpoints is not detailed. Source: Zenity: coding and personal agents · Read 27 Sep 2026
On-device controlDiffers	DescribedA single lightweight agent across Windows, macOS and Linux with one programmable policy for people and AI agents. Source: Ent press: intent-aware prevention for AI agents, 30 July 2026 · Read 13 Oct 2026	Partly describedBlocks or modifies a dangerous tool call before it executes through native agent hooks; how it reaches endpoints is not detailed. Source: Zenity: coding and personal agents · Read 27 Sep 2026
Browser extensionDiffers	DescribedBrowser-extension deployments generally available at launch. Source: Ent press: $100M seed, 16 June 2026 · Read 13 Oct 2026	Not in our sourcesNot described on the pages we read.
Network or SSE proxy	Not in our sourcesNot described on the pages we read.	Not in our sourcesNot described on the pages we read.
AI or MCP gatewayDiffers	Not in our sourcesNot described on the pages we read.	DescribedThe Zenity MCP gateway can block or modify a tool call before it executes. Source: Zenity: coding and personal agents · Read 27 Sep 2026
Names the coding agents it covers	MatchesNames OpenAI Codex, Claude Code, Claude Cowork, GitHub Copilot and Cursor. Source: Ent press: intent-aware prevention for AI agents, 30 July 2026 · Read 13 Oct 2026	MatchesNames Claude Code and Cowork, ChatGPT Codex, GitHub Copilot and Cursor. Source: Zenity: coding and personal agents · Read 27 Sep 2026
Decides on a tool call before it runsDiffers	PartlyBlocks risky agent behavior where needed; per-tool-call mechanics are not described. Source: Ent press: intent-aware prevention for AI agents, 30 July 2026 · Read 13 Oct 2026	MatchesBlocks or modifies a dangerous tool call before it executes. Source: Zenity: coding and personal agents · Read 27 Sep 2026
Controls what goes into browser AIDiffers	PartlyClassifies sensitive data at the point of use on the device and in browsers; prompt-level controls are not detailed. Source: Ent press: intent-aware prevention for AI agents, 30 July 2026 · Read 13 Oct 2026	Not in our sources
Rolls out through EDR or device management you run	Not in our sources	Not in our sources
Can warn or ask instead of only blockingDiffers	MatchesInterventions range from a soft nudge to a hard block. Source: Ent homepage · Read 13 Oct 2026	PartlyCan modify a tool call as well as block it; asking the user is not described. Source: Zenity: coding and personal agents · Read 27 Sep 2026
Can block an agent, tool or action	MatchesA hard block is one of its interventions. Source: Ent homepage · Read 13 Oct 2026	MatchesBlocks a dangerous tool call before it executes. Source: Zenity: coding and personal agents · Read 27 Sep 2026
Has a watch-only or simulation mode	Not in our sources	Not in our sources
Records who or what took each actionDiffers	MatchesNatural-language investigation timelines. Source: Ent press: intent-aware prevention for AI agents, 30 July 2026 · Read 13 Oct 2026	PartlyAI observability and agentic identity and access management are named capabilities. Source: Zenity platform · Read 27 Sep 2026
Also covers SaaS, cloud or homegrown AIDiffers	Not in our sources	MatchesIntegrations include Bedrock, Azure AI Foundry, ChatGPT Enterprise, Claude Enterprise, Copilot Studio, Vertex AI, Microsoft 365 Copilot, Power Platform, Salesforce, Agentforce and ServiceNow. Source: Zenity platform · Read 27 Sep 2026
Has a public price or tiers (vendor site or marketplace)	Not in our sources	Not in our sources
Built into	None	None
Works with	None in our sources	None in our sources
Price	Not published (demo request). Source: Ent homepage · Read 13 Oct 2026	Not published. Source: Zenity homepage · Read 27 Sep 2026

Where do they differ?

On-device control: Ent describes it; Zenity partly describes it.
Browser extension: Ent describes it; Zenity is not in our sources.
AI or MCP gateway: Ent is not in our sources; Zenity describes it.
Decides on a tool call before it runs: Ent partly matches; Zenity matches.
Controls what goes into browser AI: Ent partly matches; Zenity is not in our sources.
Can warn or ask instead of only blocking: Ent matches; Zenity partly matches.
Records who or what took each action: Ent matches; Zenity partly matches.
Also covers SaaS, cloud or homegrown AI: Ent is not in our sources; Zenity matches.

Choose Ent if

You want one policy for people and AI agents, with nudges as well as blocks
You need device and browser coverage from one agent

Choose Zenity if

Microsoft 365 Copilot, Copilot Studio, Salesforce or ServiceNow agents matter as much as laptops
You want an MCP gateway that can modify a tool call, not only block it

Which limits should you check?

Ent

Per-tool-call mechanics and rollout through MDM are not described on the pages we read.
Uses its own agent, and no price is published.

Zenity

How it reaches endpoints is not detailed on the pages we read.
No pricing published, and asking the user before an action is not described.

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