HEAD-TO-HEAD · FACTS ONLY
Bay vs Zscaler: AI endpoint control facts side by side
Short answer
Bay describes 1 of the four product control types on the pages we read and Zscaler describes 1; they differ on on-device control and network or SSE proxy. On decisions, Bay decides on a tool call before it runs and Zscaler does not describe tool-call decisions on the pages we read. 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: Bay
- Dashed teal ring: Zscaler, 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 | Zscaler |
|---|---|---|
| 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. | Zscaler's controls for employee use of generative AI: prompt-level visibility, allow or block by app, DLP blocking across GenAI apps, browser isolation that disables cut, paste and download, and data security for Microsoft Copilot. |
| 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 | Delivered with Zscaler's cloud security service in the network path; endpoint agents are not described on the page we read. Source: Zscaler: Secure the use of generative AI · Read 11 Oct 2026 |
| On-device controlDiffers | 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 | Not in our sourcesNot described on the pages we read. |
| Browser extension | 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 | Not in our sourcesNot described on the pages we read. |
| Network or SSE proxyDiffers | Not in our sourcesNot described on the pages we read. | DescribedSee all input prompts users send to apps, allow or block apps, block sensitive data with DLP across GenAI, and isolate the browser to disable cut, paste and download. Source: Zscaler: Secure the use of generative AI · Read 11 Oct 2026 |
| 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 coversDiffers | 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 | Not in our sources |
| 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 | Not in our sources |
| Controls what goes into browser AIDiffers | Not in our sources | MatchesPrompt-level visibility, DLP blocking across GenAI apps, and browser isolation that disables cut, paste and download. Source: Zscaler: Secure the use of generative AI · Read 11 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 blockingDiffers | MatchesAsk is one of three answers, with Allow and Deny. Source: Bay homepage · Read 27 Sep 2026 | Not in our sources |
| 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 | MatchesAllow or block GenAI apps, and block sensitive data with DLP. Source: Zscaler: Secure the use of generative AI · Read 11 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 actionDiffers | 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 | Not in our sources |
| Also covers SaaS, cloud or homegrown AIDiffers | Not in our sources | PartlyData security for Microsoft Copilot, including misconfigurations. Source: Zscaler: Secure the use of generative AI · Read 11 Oct 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. 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: Zscaler: Secure the use of generative AI · Read 11 Oct 2026 |
Where do they differ?
- On-device control: Bay describes it; Zscaler is not in our sources.
- Network or SSE proxy: Bay is not in our sources; Zscaler describes it.
- Names the coding agents it covers: Bay matches; Zscaler is not in our sources.
- Decides on a tool call before it runs: Bay matches; Zscaler is not in our sources.
- Controls what goes into browser AI: Bay is not in our sources; Zscaler matches.
- Rolls out through EDR or device management you run: Bay matches; Zscaler is not in our sources.
- Can warn or ask instead of only blocking: Bay matches; Zscaler is not in our sources.
- Has a watch-only or simulation mode: Bay matches; Zscaler is not in our sources.
- Records who or what took each action: Bay matches; Zscaler is not in our sources.
- Also covers SaaS, cloud or homegrown AI: Bay is not in our sources; Zscaler partly matches.
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 Zscaler if
- You already route traffic through Zscaler and want GenAI controls there
- Your main risk is sensitive data pasted or uploaded into GenAI web apps
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.
Zscaler
- Coding agents, MCP servers and local agent actions are not described on the page we read.
- Warn or ask responses are not described, and no pricing is published.