LAO
Local AI Workflow Orchestrator - Chain local AI models together like whispering agents in a secure lab. Run audio transcription, summarization, and refactoring—all offline with no cloud dependencies.
Status
Active Development
Started
2025
Primary Language
Rust
Last Updated
2025
LAO (Local AI Workflow Orchestrator) is a cross-platform desktop tool built for developers who want to chain local AI models together like whispering agents in a secure lab. It's a DAG engine for workflows, a plugin system for community-powered agents, and an orchestration layer for your offline AI stack. Think of it as Zapier and Node-RED having a hacker baby powered by Ollama and Whisper.cpp.
Developers deserve tools that respect their data, run at local speed, and don't lock them into SaaS pricing. Current AI workflow tools require cloud dependencies, have privacy concerns, and lack the flexibility needed for complex local AI orchestration. There's a need for a local-first solution that can chain multiple AI models together while maintaining complete data privacy and control.
LAO provides a comprehensive local AI orchestration platform with modular plugins for different AI models, offline DAG execution with dependency ordering and retries, hybrid CLI and GUI interfaces, and a local-first architecture that never phones home. The tool supports various AI models like Whisper, Mistral, and custom tasks through a composable plugin system.
- Modular plugin system for local AI runners (Whisper, Mistral, custom tasks)
- Offline DAG execution with dependency ordering, retries, and validation
- Hybrid CLI + GUI with Tauri-powered visual flow builder
- Typed YAML workflows for reproducible AI pipelines
- Local-first architecture with complete data privacy
- Cross-platform support (macOS, Linux, Windows)
- Real-time workflow monitoring and logging
- Community-powered plugin ecosystem
Key challenges included designing a flexible plugin architecture that supports various AI models, implementing efficient DAG execution with proper dependency management, creating a user-friendly interface that works for both technical and non-technical users, ensuring cross-platform compatibility across macOS, Linux, and Windows, and optimizing performance for local AI model execution without cloud dependencies.
- Advanced AI model integration (GPT-4, Claude, custom models)
- Real-time collaboration features for team workflows
- Advanced workflow debugging and profiling tools
- Integration with popular development tools and IDEs
- Cloud sync for workflow templates (optional)
- Advanced scheduling and automation features
- Performance optimization for large-scale workflows
- Mobile companion app for workflow monitoring