open-jarvis
OpenJarvis is an open-source framework for building personal AI agents that run entirely on-device, prioritizing privacy and hardware efficiency.
At a Glance
- AI Researchers
- Open-source Developers
- Privacy-conscious Consumers
AI Tools by open-jarvis
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OpenJarvis
Local AI Agent Framework
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Products & Services
An open-source Python framework for building personal AI agents that run locally on consumer hardware.
A Tauri-based desktop application for macOS, Linux, and Windows for interacting with local AI agents.
A browser-based interface for managing agents, monitoring energy efficiency, and visualizing cost savings.
Market Position
Differentiates itself from cloud-heavy frameworks like OpenAI's Swarm or Microsoft's AutoGen by focusing on local-first, on-device compute and efficiency metrics.
Leadership
Founders
Jon Saad-Falcon
Ph.D. candidate in Computer Science at Stanford University; previously worked at Databricks, AI2, and GeorgiaTech. Co-Creator and Co-Lead of OpenJarvis.
Avanika Narayan
Ph.D. student at Stanford University; focused on machine learning and scaling intelligence. Co-Creator and Co-Lead of OpenJarvis.
Christopher Ré
Associate Professor at Stanford University, lead of Hazy Research lab. MacArthur Fellow and co-founder of several AI startups (Lattice Data, Snorkel AI).
Azalia Mirhoseini
Assistant Professor at Stanford University; previously a research scientist at Google Brain. Expert in AI for systems and hardware-software co-design.
Executive Team
Jon Saad-Falcon
Co-Creator and Co-Lead
Stanford Ph.D. Candidate, leads OpenJarvis development.
Avanika Narayan
Co-Creator and Co-Lead
Stanford Graduate Researcher, leads framework architecture.
Board of Directors
Founding Story
OpenJarvis emerged from research at Stanford into 'Intelligence Per Watt,' which demonstrated that local AI could handle most queries efficiently. The project was started to provide private, local-first alternatives to cloud-based AI assistants.
Business Model
Revenue Model
Open-source (Apache 2.0 License); funded by academic research grants from Stanford University and corporate partners.
Pricing Tiers
Available for free under Apache 2.0 license.
Target Markets
- AI Researchers
- Open-source Developers
- Privacy-conscious Consumers
- Privacy-sensitive personal AI triage (email, calendar)
- Local knowledge bases for research and document QA
- Automated agentic workflows (code review, summaries)
- On-device AI experimentation for researchers
- Stanford University
- Research Community
- Ollama users