Breathe-Memory – Associative memory injection for LLMs (not RAG)
LLMs forget. The standard fix is RAG — retrieve chunks, stuff them in. It works until it doesn't: irrelevant chunks waste tokens, summaries lose structure, and nothing actually models how memory works. Breathe-memory takes a different approach: associative injection. Before each LLM call, it extracts anchors from the user's message (entities, temporal references, emotional signals), traverses a concept graph via BFS, runs optional vector search, and injects only what's relevant — typically in <60ms. When context fills up, instead of summarizing, it extracts a structured graph: topics,…
Breathe-Memory – Associative memory injection for LLMs (not RAG) launched on March 26, 2026 with 6 votes, #1,631 of 23,380 launches that month and more than 75% of that year's launches.
What it does
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In the maker’s words, at launch
LLMs forget. The standard fix is RAG — retrieve chunks, stuff them in. It works until it doesn't: irrelevant chunks waste tokens, summaries lose structure, and nothing actually models how memory works. Breathe-memory takes a different approach: associative injection. Before each LLM call, it extracts anchors from the…
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