Athena – Portable, platform-agnostic AI memory stored locally

Summary: Athena is a local-first AI memory framework that stores context in user-owned Markdown files. It uses a hybrid RRF search combining Vector, GraphRAG, and Keyword methods, supported by a 150+ protocol library and a bionic architecture that compounds knowledge over time.

What it does

Athena manages AI memory by saving data locally in Markdown files and enables deep retrieval through hybrid search techniques. It supports portability across models and platforms without relying on external services.

Who it's for

It is designed for users seeking a sovereign, platform-independent AI memory system to build and maintain compound knowledge.

Why it matters

Athena solves the problem of losing context with each AI session by providing persistent, user-controlled memory accessible across platforms.