Features
Run AI coding agents in isolated sandboxed environments
Unified API to swap between Claude Code, Codex, OpenCode without code changes
Multi-repo support: agents can reason across frontend, backend, workers, infra, shared packages
Full infrastructure: install packages, run Docker, seed databases, start dev servers, execute tests
Warm dev environment: repo cloned, dependencies installed, services running before task starts
Support for any model: route hard tasks to frontier models, routine work to open-source models (Qwen, Kimi, GLM)
Event-driven triggers: GitHub PR, Slack message, Linear issue spin up isolated agent instance
Automation of recurring tasks: triage incidents, check cloud resources, update docs, follow up on issues
MCP server support for custom workflow integrations
Open-source TypeScript SDK on GitHub
Bring your own API keys (on Pro, Max, Enterprise)
Larger machines available on Max and Enterprise plans
Private cloud deployment in your VPC (Enterprise)
Live knowledge graph from code, commits, issues, and docs
Feasibility analysis: flags buildable vs risky items
Technical design document generation grounded in service topology
Impact assessment maps services, APIs, and dependencies across repos
Auto-scoping epics into Jira/Linear stories with effort estimates
One-shot production code generation grounded in service patterns
AI code reviews with cross-repo impact analysis
Production issue triage via MCP
Conversational learning from Slack and Jira
Accelerated onboarding via system-level Q&A in coding agents
Create Jira tickets and merge requests from Slack
MCP server for integration with Cursor, Claude Code, Codex
On-prem or cloud deployment
No code storage or model training
