How ɳClaw works
Infinite memory, auto-topic detection, Rust-powered retrieval, and 13 plugins — composing into one conversational AI that knows your life.
Infinite memory
Every conversation, remembered forever
Most AI assistants forget everything when you close a chat window. ɳClaw stores every conversation in a Postgres knowledge graph powered by pgvector and the ltree extension. When you ask about something you discussed three months ago, ɳClaw finds it via semantic vector search and pulls the relevant context into the prompt window.
- Every message stored with embedding in your own Postgres
- Full-text and vector search across your entire conversation history
- Context window automatically assembled from relevant past conversations
- No external cloud storage — your data stays on your server
Technical details
- Storage
- Postgres 16 + pgvector 0.7
- Hierarchy
- ltree topic paths
- Search
- MeiliSearch + vector cosine similarity
- Context assembly
- Rust (libnclaw) — chunked, scored, deduped
Auto-topic detection
No "New Chat" button, ever
After 3 messages in a conversation, ɳClaw classifies the topic using the AI plugin. The topic becomes an ltree path in your knowledge graph. Related conversations are automatically linked via pgvector similarity. The sidebar shows your life organized by subject, not by timestamp — and it builds itself without any manual tagging.
- Topic auto-assigned after 3 messages — no manual categorization
- Topics stored as ltree paths: /work/project/feature, /health/fitness
- Related topics linked automatically when vector similarity exceeds threshold
- Entire knowledge tree browsable in sidebar by subject, not date
Technical details
- Trigger
- Message 3 in any conversation
- Classification
- AI plugin (configurable model)
- Storage
- ltree path in np_topics table
- Linking
- pgvector cosine similarity > 0.85 threshold
Rust core
Native speed for embedding and retrieval
ɳClaw's embedding pipeline and knowledge graph retrieval are implemented in a Rust library called libnclaw. This Rust core handles chunking, embedding, vector scoring, and ltree path resolution. It ships as a native library in the macOS and Linux desktop builds via Tauri, and as an FFI module in the mobile builds. No Python overhead on critical paths.
- libnclaw Rust library handles all embedding and retrieval on critical paths
- Tauri desktop apps on macOS, Windows, and Linux include the native binary
- Mobile apps use Rust via FFI — no JavaScript bottleneck for vector ops
- Chunking strategy is topic-aware — splits at sentence and paragraph boundaries
Technical details
- Library
- libnclaw (MIT, nself-org/nclaw)
- Desktop integration
- Tauri 2 — native sidecar
- Mobile integration
- FFI — React Native module
- Embedding model
- Configurable — local GGUF or OpenAI-compatible API
Plugin ecosystem
13 plugins compose into a full personal assistant
The ɳClaw bundle ships 13 nSelf plugins. Each plugin extends ɳClaw's conversational surface with a new capability. The mux plugin routes structured tool calls to the right plugin. All plugins communicate over the same Postgres bus, so context and memory flow across capabilities automatically.
- ai: reasoning, multi-turn, system prompt configuration
- claw + claw-web: the ɳClaw memory and knowledge graph engine
- mux: intent routing — the conversational API gateway
- google: Gmail read/write, Calendar events, Drive search
- voice: speech-to-text and text-to-speech via Whisper-compatible API
- browser: headless Chrome control for web research and form filling
- notify: push notifications to mobile via FCM
Technical details
- Bundle size
- 13 plugins
- Router
- mux plugin — intent-based tool routing
- Licensing
- $0.99/mo — ɳClaw bundle or ɳSelf+
- Open source
- Core plugins MIT; pro plugins license-gated
Full data sovereignty
Your data never leaves your server
ɳClaw runs on your own VPS or local machine. Postgres, pgvector, Redis, Hasura, and the embedding pipeline all run on infrastructure you control. The MIT client apps connect to your own backend — there is no ɳSelf-operated server in the data path for any conversation content.
- All conversation data stored in your own Postgres instance
- Embedding API calls go to your chosen provider — not through nSelf
- nSelf CLI manages the backend locally — no remote shell access required
- Open source client apps — audit the code that talks to your server
Technical details
- Backend
- Self-hosted via nSelf CLI
- Hosting
- Any Linux VPS — Hetzner, DigitalOcean, your own hardware
- AI model
- Your choice — OpenAI API, local GGUF, any OpenAI-compatible endpoint
- Sync
- Optional — all local by default
Ready to try ɳClaw?
MIT licensed, free to download. Add the $0.99/mo ɳClaw bundle to enable all 13 backend plugins and the full infinite memory stack.