Aixle Flow — orchestrate coding agents through durable, inspectable workflows.
The team-level control plane for AI coding agents. Put a card on the board, an agent picks it up in an isolated container, your team sees the run, the cost, and the output — without anyone opening a terminal.
Cursor and Claude Code are personal superpowers. They run on your laptop, in your terminal, for your task. Once more than one person on a team starts delegating work to agents, the wheels come off:
- Nobody knows what's running, where, or whether it's stuck. - There's no shared trail of what an agent did or how much it cost. - Setup is per-developer, so the team uses agents five different ways.
Aixle Flow is the layer above the agent — the Kanban board, the workflow graph, the audit log, the cost meter. The agent stays great at coding; Aixle Flow makes it usable by a team.
It is the only open platform we know of that combines:
- A board with column → workflow bindings (drop a card, trigger a run) - A DAG workflow engine with retries, approval gates, and parallel steps - Container-isolated agent execution (Claude Code, Cursor CLI, Codex, Gemini CLI) - MCP-native tool integration - Per-session cost tracking in tokens and cents - Temporal under the hood for durable, long-running runs
Three commands to a working app on http://localhost:4000.
5-minute setup is on the roadmap. Right now make setup builds agent images which takes longer the first time. See ROADMAP.md for the planned docker compose up single-command flow.
From the project README.
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Turn the agent CLIs you already use into shared services your whole team can call. Natural-language-driven agent orchestration for Claude Code, Cursor Agent, and OpenAI Codex.
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