Infrastructure

Self-hosted AI systems your team can control.

Own the orchestration, data path, configuration, workspaces, and integrations without pretending every model must run locally.

What self-hosted means

Self-hosted does not mean every model runs locally. It means the orchestration layer, configuration, data path, logs, workspaces, and integrations run on infrastructure the client controls. Model APIs may still be external when they are the right technical choice.

Typical architecture

  • A host process receives messages and owns credentials
  • Per-session or per-agent containers isolate execution
  • Only approved workspaces and context are mounted
  • Memory and databases remain behind the host boundary
  • Health checks, logs, backups, and restart policies support operation

Security boundaries

Container isolation is one layer, not a complete security promise. A production design also needs scoped mounts, network policy, secret handling, permission review, input validation, tool allowlists, logging, updates, and an incident path.

Deployment options

Depending on workload and access requirements, systems can run on a Linux VPS, a dedicated server, or local hardware such as a Mac mini. The choice should follow data sensitivity, uptime, channel connectivity, and maintenance capacity.

Start with the workflow

Turn the manual work into a system.

Describe what happens today, where it slows down, and what a successful result should look like.