HEAD-TO-HEAD · FACTS ONLY
Bay vs Ent: AI endpoint control facts side by side
Short answer
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: Bay
- Dashed teal ring: Ent, 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)
What are the facts, side by side?
| Fact | Bay | Ent |
|---|---|---|
| Owner | None | None |
| Positioning | An endpoint-first control layer for AI agents, coding assistants and MCP servers on employee devices. Bay describes itself as a fully preventive, agentless platform that classifies, governs and prevents risks across every AI agent and tool on enterprise endpoints. | 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. |
| How it reaches devices | Deploys through your existing EDR or MDM, with no new agents and no new tools; Bay says it scans in minutes and exits cleanly. Source: Bay homepage · Read 27 Sep 2026 | 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 |
| On-device control | DescribedInventories AI agents, MCP servers, tools, credentials and extensions on the device, and its Enforcer returns Allow, Ask or Deny locally on prompts, pre-tool calls and post-tool responses on supported agent surfaces. Delivered as Wave, an ephemeral binary that runs through your existing MDM or EDR. Policies can be scoped by agent, group, endpoint or device. Source: Bay blog: Ghostjacking (re-read) · Read 11 Oct 2026 | 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 |
| Browser extensionDiffers | Not in our sourcesNo browser extension is described. Bay's Application Control can allow or block browsers and extensions as applications, which is a device rule, not a control on what goes into browser AI. Source: Bay blog: Ghostjacking (re-read) · Read 11 Oct 2026 | DescribedBrowser-extension deployments generally available at launch. Source: Ent press: $100M seed, 16 June 2026 · Read 13 Oct 2026 |
| 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 gateway | Not in our sourcesNot described on the pages we read. | Not in our sourcesNot described on the pages we read. |
| Names the coding agents it covers | MatchesManaged settings for Claude Code, Codex and Claude Desktop lock permission rules, preserve managed hooks, restrict MCP servers and constrain plugin sources. Source: Bay blog: Ghostjacking, an AI agent attack (August 2026) · Read 27 Sep 2026 | 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 |
| Decides on a tool call before it runsDiffers | MatchesEvaluates prompts, pre-tool calls and post-tool responses and returns Allow, Ask or Deny locally, which Bay states takes under 4ms with no cloud round-trip, on supported agent surfaces. Source: Bay blog: Ghostjacking (re-read) · Read 11 Oct 2026 | 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 |
| Controls what goes into browser AIDiffers | Not in our sources | 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 |
| Rolls out through EDR or device management you runDiffers | MatchesDeploys through your existing EDR or MDM; no new agents. Source: Bay homepage · Read 27 Sep 2026 | Not in our sources |
| Can warn or ask instead of only blocking | MatchesAsk is one of three answers, with Allow and Deny. Source: Bay homepage · Read 27 Sep 2026 | MatchesInterventions range from a soft nudge to a hard block. Source: Ent homepage · Read 13 Oct 2026 |
| Can block an agent, tool or action | MatchesDeny stops an action. Rules cover MCP servers (an allow or block list, and per-tool rules for read, create, update, delete and execute), applications, CLIs, browsers, IDEs and extensions, credentials and files, network egress allow lists, and capability rules such as shell execution, package installation and cloud CLIs. Source: Bay blog: Ghostjacking (re-read) · Read 11 Oct 2026 | MatchesA hard block is one of its interventions. Source: Ent homepage · Read 13 Oct 2026 |
| Has a watch-only or simulation modeDiffers | MatchesSimulation Mode runs a rule without enforcing it. Source: Bay blog: Ghostjacking, an AI agent attack (August 2026) · Read 27 Sep 2026 | Not in our sources |
| Records who or what took each action | MatchesRecords who triggered an action, whether a human was involved, and the chain from prompt to system action. Source: Bay homepage · Read 27 Sep 2026 | MatchesNatural-language investigation timelines. Source: Ent press: intent-aware prevention for AI agents, 30 July 2026 · Read 13 Oct 2026 |
| Also covers SaaS, cloud or homegrown AI | Not in our sources | Not in our sources |
| 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. Bay's site has a demo request and no pricing page (re-checked 11 October 2026). Source: Bay homepage (re-read) · Read 11 Oct 2026 | Not published (demo request). Source: Ent homepage · Read 13 Oct 2026 |
Where do they differ?
- Browser extension: Bay is not in our sources; Ent describes it.
- Decides on a tool call before it runs: Bay matches; Ent partly matches.
- Controls what goes into browser AI: Bay is not in our sources; Ent partly matches.
- Rolls out through EDR or device management you run: Bay matches; Ent is not in our sources.
- Has a watch-only or simulation mode: Bay matches; Ent is not in our sources.
Choose Bay if
- Your developers run coding agents with many MCP servers and you want a decision on each action before it runs
- You want to add AI agent control through the EDR or MDM you already run instead of rolling out another agent
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
Which limits should you check?
Bay
- Endpoint only: no browser extension, network proxy or AI gateway is described, and nothing on SaaS or cloud-hosted AI apps.
- One of the smallest public footprints here: a single homepage, two blog posts, no documentation portal and no published pricing (re-checked 11 October 2026).
- Headline figures such as under 5 minutes to deploy, under 1% false positives and 100% of shadow AI discovered are Bay's own statements and have not been verified.
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.