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A household shares a computer.

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A team shares a workspace.

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A hosted service supports different organizations.

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Open Swarm brings applications and agents together,

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while giving identity, permissions, and configuration a

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place in the architecture.

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These are applications you can see and

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use.

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Edit the document yourself.

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Or work side by side with its

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embedded concierge and ask it to make

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the change.

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Agents can coordinate supported actions across applications,

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using the permissions of the person doing

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the work.

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Multi-user means separate identities inside a workspace.

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Multi-tenant adds a boundary between workspaces.

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The kernel carries the caller and tenant

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through admitted work, and applies scoped access

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to records and resources.

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A second tenant is not simply another

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browser tab.

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Users can bring their own supported provider

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credentials.

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The payment resolver can select the caller’s

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key, then the tenant’s key, then an

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administrator-funded pool within its cap.

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This is separate from choosing the model.

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Credentials stay behind access controls; the spending

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record identifies the payer.

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An administrator can configure fleet defaults.

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A bot can have its own supported

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provider and model configuration.

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A permitted user choice can take precedence

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for a turn.

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The harness determines how the agent runs.

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Persistent per-user, per-bot harness controls depend on

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the installed runtime; a preference never grants

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extra access.

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Image generation, speech, transcription, and video also

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need providers.

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Configure the capabilities your installation offers, with

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the available defaults and personal choices.

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Check availability, credentials, and cost for each

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capability.

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Choosing a text model does not automatically

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configure every creative tool.

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Routing answers a different question: which bot

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should do this work?

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Jarvis or a configured workflow can hand

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a task to the appropriate specialist.

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That bot uses its resolved configuration and

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permitted tools.

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Useful context can move with the task,

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without making everyone’s private data available to

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every bot.

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Give each person their own login.

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Grant access to the applications and resources

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they need.

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Share a supported knowledge collection or workspace

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through its access controls, and keep other

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material private.

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User and tenant isolation protects application access;

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it is not a promise that the

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administrator of the host cannot access the

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machine.

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Run a supported deployment at home or

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on larger infrastructure.

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A laptop can use an external model,

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while a capable machine can host a

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suitable local model.

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External providers receive the context you send.

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Keeping processing, inference, and storage local is

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what lets that information remain on your

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computer.

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The difference is the combination: usable applications,

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embedded concierges, coordinating agents, and explicit control

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over who can act, which intelligence they

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use, and where the work runs.

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Explore the technical and home setup guides

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at oswarm.ai.