Levh is an innovative, local-first memory layer designed specifically for AI agents and human workflows. In an era where AI tools often rely on cloud infrastructure, Levh takes a privacy-focused approach by operating entirely without cloud accounts or telemetry.
The tool seamlessly captures context from a wide array of sources including conversations, projects, files, emails, calendars, and MCP (Model Context Protocol) tools. By processing this information, Levh builds an inspectable knowledge graph that maps out relationships and data cleanly.
Key capabilities include surfacing trust and conflict signals to ensure accuracy, as well as allowing stale details to naturally fade over time, keeping memory relevant and up to date for your AI workflows.
Levh is a local-first memory layer for AI agents and humans that captures context from various sources like files, emails, calendars, and MCP tools to build an inspectable knowledge graph.
No, Levh operates completely without cloud accounts or telemetry, ensuring a local-first and privacy-focused experience.
Levh is available as an open-source project and can be found via its GitHub repository.
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