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Open-source workspace for building AI agents from a visual canvas, a prompt, or code
Sim is a workspace for building and running AI agents. An agent is assembled on a visual canvas, described in a prompt, or written in code, and can reach more than a thousand integrations and every major model provider. The platform carries the supporting parts too: knowledge bases, data tables, file storage shared between team and agents, and execution logs and traces for debugging. The code is open source on GitHub, with roughly 29.5k stars and a self-hosting path. The hosted service is metered in credits and sold per seat, from a free tier of 1,000 monthly credits up to $100 per user per month, with SSO, access control and SOC2 features reserved for a quoted Enterprise tier. The terms name Sim, Inc. under United States law.
Free gives 1,000 credits a month, one workspace, 10 concurrent executions and 30-day log retention. Pro is $25 per user per month for 6,000 credits plus a 50/day refresh, three workspaces and unlimited log retention. Max is $100 per user per month for 25,000 credits. Enterprise adds SSO, access control and self-hosting support and is quoted.
Use tool ↗Sim covers the unglamorous half of agent work — memory, tables, file storage, logs — in the same place you draw the workflow, and the open repository means you can host it yourself if the meter bothers you. The meter is the catch: credits are the unit of everything, and an agent that loops or fans out consumes them faster than the per-seat headline suggests.
Watch out: The pricing page lists credits per user but concurrency as a flat plan-level number, so a busy shared workspace can hit the execution ceiling long before it runs out of credits — confirm which limit applies before committing.
Side-by-side fact sheets against the competitors our research names — pricing, platforms, API and both verdicts on one page.
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