Epismo OS
Freemium
Teams using multiple AI tools on the same tasks
When you're running three or four AI agents across a project, tracking what each one is doing — and what they produced — turns into a tab-management nightmare that no spreadsheet or Notion page fixes cleanly. Biom is a visual workspace built to hold that context in one place.
$20/mo · Free tier: 10 assistant actions a month, 30 minutes of MCP cloud time a day, 10 images a month for your cards · Checked Oct 31, 2026
Biom positions itself as the single source of truth for teams running multiple AI agents alongside human collaborators, letting you see automations, tools, and outputs in one canvas rather than hunting across chat logs and terminal windows. The vendor describes support for Gemini CLI, which means agents you're already running from the command line can surface their work inside the workspace. A daily digest view suggests the tool is designed around ongoing, background agent activity rather than one-shot runs. Where the edges show: the scraped page offers precious little detail about how deeply agents integrate, what happens when a workflow errors mid-run, or how branching logic is expressed visually. Teams with complex conditional pipelines will hit those unknowns fast.
Bottom line: Biom earns its place on a team that wants a shared dashboard for agent outputs and automations — but if your workflows branch based on what the last step returned, the visual model's limits will surface before you've finished the second project.
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Freemium
Teams using multiple AI tools on the same tasks
Paid
E-commerce and retail businesses
Biom is a visual workspace designed to centralize AI agent activity, automation tools, and team collaboration under a single interface. The core workflow, as described by the vendor, involves agents running tasks in the background while humans and agents work on shared artifacts — the example given on the page is a design document — with all of that activity visible in one place rather than scattered across terminals, chat threads, and separate documents.
The standout differentiator is the Gemini CLI integration. Rather than forcing teams to abandon command-line tooling and rebuild everything inside a proprietary agent framework, Biom is positioned to ingest work already happening via CLI agents — which means adoption does not require a full migration. You bring your agents; the workspace manages the visibility layer.
Biom fits teams that are already running agents and have lost track of what those agents are doing or producing. The daily digest framing suggests it handles ongoing, persistent automation rather than triggered one-off tasks. Where it breaks: the publicly available information describes no API access, no self-hosted option, and no detail on how conditional logic or branching is expressed in the visual model — which means teams whose automations depend on branching based on step outputs are building on unverified ground.
No API is available, so embedding Biom’s workspace data into other internal tools or pipelines is not an option. Self-hosting is also absent, which rules it out immediately for teams with data residency requirements.
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