conch

Biological memory for AI agents. Semantic search + decay, no API keys needed.

The Problem

Most AI agents use a flat memory.md file. It doesn't scale:

• Loads the whole file into context — bloats every prompt as memory grows
• No semantic recall — grep finds keywords, not meaning
• No decay — stale facts from months ago are weighted equally to today's
• No deduplication — the same thing gets stored 10 times in slightly different words

You end up with an ever-growing, expensive-to-query, unreliable mess.

Why Conch

Conch replaces the flat file with a biologically-inspired memory engine:

• Recall by meaning — hybrid BM25 + vector search finds semantically relevant memories, not just keyword matches
• Decay over time — old memories fade unless reinforced; frequently-accessed ones survive longer
• Deduplicate on write — cosine similarity (0.95) detects near-duplicates and reinforces instead of cloning
• No infrastructure — SQLite file, local embeddings (FastEmbed, no API key), zero config
• Scales silently — 10,000 memories in your DB, 5 returned in context. Prompt stays small.

Install

No Cargo? See the Installation Guide for prebuilt binaries and build-from-source instructions.