ori-memory

You can create persistent memory across sessions using a Markdown-based knowledge graph to store and retrieve durable insights, decisions, and goals for long-running AI workflows.

A markdown knowledge graph for AI memory retrieval stores durable notes and decision histories, enabling learning retrieval to revisit insights weeks or months later across different projects.

Yes, a local Node.js environment is required to initialize the memory vault, install dependencies, and operate the session lifecycle through the CLI and bridge.

You can capture a key insight to your vault using the add command and promote it later using the promote command to elevate important notes within the knowledge graph.

Yes, persistent memory can be applied to long-running research projects and decision histories, ensuring that identity, goals, and methodology are preserved and revisited later.

Markdown-based knowledge graph persistence requires a local Node.js environment and specific CLI tools to operate, meaning it is designed for local session workflows rather than distributed cloud environments.