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Simular subscription

Simular AI

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Plans

Plus

  • 10,000 reloadable credits
  • One developer agent per computer
  • Runs on macOS and Windows
  • The workflow editor in developer mode
  • Sharing workflows in the community gallery, plus community support

Pro

  • Unlimited agent credits
  • One deployment agent included
  • Support for running on virtual machines
  • Private and team workflow sharing
  • Full Simulang support
  • Zero data retention on the model providers' side
  • Priority engineering support

Enterprise

  • Unlimited credits with managed scaling
  • All platforms, virtual machines and private cloud
  • An advanced workflow editor with custom extensions
  • Team collaboration and audit logs
  • SOC 2, HIPAA, SSO and role-based access control
  • A dedicated account and engineering team

Plan contents as published by the vendor; seller prices arrive at launch.

What you get

A Simular subscription is issued to your own email and the agent installs on your computer: workflows, memory and run records stay with you. Check the plan and the number of machines — billing is per computer, and the plan decides credits, virtual-machine support and team workflow sharing. The seller states the next charge date at delivery, and it is visible in the dashboard.

About the service

Sai, the agent from the Simular research team, handles a computer the way a person does: it looks at the screen, moves the cursor, types, opens native apps and the browser, and writes code or runs terminal commands where that is easier. The app runs on macOS with a Windows build announced, and long jobs can be moved onto an isolated virtual desktop that stays awake and keeps working without you. Before critical steps the agent stops and asks for confirmation, and the workflows it builds can be edited in a visual editor or in Simular's own Simulang language. Underneath sits the Agent S line the team has developed out of its research: the vendor publishes results on the OSWorld, WebVoyager and AndroidWorld benchmarks but does not name the underlying language models. It suits work that needs real actions in applications and on websites rather than a conversation — back-office routine above all.

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