# Neonmem 0.9.7 is out. > Source: > Published: 2026-06-24 16:34:22+00:00 ## 1. A two-level importer — two kinds of "stuff," treated differently The big change. Your project doesn't come in one shape, so the importer no longer flattens it into one pile: - **Folders & files → a searchable knowledge pool.** Your docs, code and notes are vectorised into a lossless, deduplicated facts pool — the same fact stated three ways becomes one fact, every source kept. Nothing is summarised away. - **Agent chats → typed memories.** Point Neonmem at a Claude (or other agent) transcript and it pulls out only what's worth keeping — the **decisions, dead-ends and rules** — as clean, typed memories. A decision is stored as a decision; a dead-end stays a warning. The process-narration ("I read the file…", "please check…") is dropped. - **Links become knowledge.** If a chat references a file on disk, that file is pulled into the pool automatically, with a memory that points back to it. The result is labelled honestly in the UI: **Facts loaded** (the pool) and **Memories created** (the kept decisions). ## 2. Grounded, offline recall 0.9.7 replaces the old embedder with **IBM Granite-30M**, run as a fused **fp16 ONNX** graph through **ONNX Runtime**: - Database-class retrieval quality on **any CPU** — no GPU, no PyTorch, no API key, no cloud. - Every prompt walks memory in order — **reflexes → short-term → long-term → facts pool** — and answers from what you actually imported, or **honestly says it doesn't know**. This is the headline behaviour: ask *"what is ARC?"* and you get **your** definition from **your** docs — not the textbook expansion the model would otherwise guess. A memory that's occasionally wrong is worse than no memory at all, so the rule is: answer from the user's sources, or abstain. Never invent. ## 3. Tags that stick Tag an import with a topic (e.g. `Specific API` ) and Neonmem mints **one clean, canonical** memory for it, linked back to the source — *even when your docs never write the term* verbatim, as long as they clearly describe it. If the corpus genuinely has nothing on a tag, it's left out rather than faked. ## 4. Clean by construction Memories follow one **golden rule**: a single concise statement (`ARC — your provisioning` platform ) linked to the full source, not a messy pile of raw chunks. Chat capture deduplicates through the same facts layer, so re-importing a conversation never doubles up. ## 5. One durable cartridge - The importer keeps the **full source corpus** inside the cartridge (content-addressed + compressed) — one file replaces the scattered docs and transcripts, and the facts are always rebuildable from ground truth. - **Opt-in AES-256-GCM encryption at rest** — your whole corpus as a private vault. - Imported knowledge is long-term and **survives reopening** the project. ## Built on (all open, permissively licensed) Embeddings: **IBM Granite-30M** (Apache-2.0) via **ONNX Runtime** (MIT). Vector search: **FAISS** (MIT). Agent integration: the **Model Context Protocol**. Full attributions ship with every download. No third-party LLM, nothing phones home. ## Get it Windows (signed installer + portable) and Linux (AppImage); macOS on the way. Local, private, and free for personal use. → [neonmem.com](https://neonmem.com) *Import a project, then ask it the one thing your assistant always gets confidently wrong* about your codebase. That question is the whole test.