OpenJarvis
Stanford's open-source framework for building personal AI agents that run entirely on-device with tools, memory, and learning capabilities.
OpenJarvis tackles the privacy nightmare of cloud-based AI agents by keeping everything local. Stanford’s Scaling Intelligence Lab built this framework to run personal AI assistants entirely on your device.
The framework goes beyond just model execution. It includes the full software stack needed for agent deployment: tool integration, persistent memory systems, and continuous learning capabilities. This means your agent can remember past interactions and improve over time without sending data to external servers.
We like this approach because it addresses real concerns about AI agent adoption. Many organisations won’t deploy agents that phone home with sensitive data. OpenJarvis gives developers a path to build capable personal assistants whilst maintaining complete data control.
The timing feels right too. Local inference is getting faster and cheaper. Having a robust framework that handles the plumbing means developers can focus on building useful agent behaviours rather than wrestling with infrastructure.
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