Rebyte Documentation
Rebyte runs parallel AI agents in the cloud. Each agent gets its own agent computer -- an isolated cloud computer with dedicated CPU, memory, and disk. Describe what you want built, pick an agent, and let it work with full git integration and access to your organization's data.
Product Guide
Learn how Rebyte's core components fit together.
Agent Execution
How agents run -- agent computers, agents, skills, and security.
- Agent Execution Overview -- Agent computers, agents, and skills
- Projects & Tasks -- How projects, tasks, and agent computers relate to each other
- Task Operations -- Create, monitor, and manage coding tasks
- Agents -- Claude Code, Gemini CLI, Codex, and Rebyte compared
- Security -- Isolation model, network policies, and data handling
Context Lake
Connect your data so agents can query it.
- Context Lake -- Connect your databases, files, and warehouses so agents can query your business data with SQL
- Supported Sources -- Every connector, organized by category
- Access Control -- Permission model and practical examples
Rebyte Cloud
- Rebyte Cloud -- Deploy the apps your agents build to
*.rebyte.prowith zero config
Rebyte API
Automate everything programmatically.
- API Overview -- Endpoints, authentication, and quick start
- Authentication -- API keys and request signing
- Files -- Upload files for your tasks
- Tasks -- Create, list, poll, and follow up on tasks
- Webhooks -- Get notified when tasks complete
FAQ
Common questions and answers: FAQ