Intelligent Memory Infrastructure for AI Agents
An evolution of the Memento knowledge graph system (Neo4j/MCP) into a dynamic intelligent memory platform. Self-hosted, transparent, and sovereign.
- Neo4j — Graph database with vector indexes for semantic search
- MCP Server — Model Context Protocol server for AI agent integration
- n8n Workflows — Orchestration for ingestion, relation classification, and maintenance
- text-embedding-3-large — 3072-dimension embeddings for high-quality semantic search
| Concept | Description |
|---|---|
| Document | Raw content ingested (PDF, URL, text, audio, etc.) |
| Memory | Atomic fact extracted from a Document with embeddings and temporal metadata |
| Relations | Intelligent links between memories: UPDATES, EXTENDS, DERIVES |
- Intelligent Relations — Auto-detect updates, extensions, and derivations between memories (CRITICAL)
- Automatic Forgetting — Time-based decay, episode expiry, preference reinforcement (CRITICAL)
- Multimodal Ingestion — PDF, URL, image, video, audio, conversation pipelines (HIGH)
- SuperRAG — Hybrid search, reranking, query rewriting, contextual chunking (HIGH)
- User Profiles — Auto-generated static + dynamic user profiles (MEDIUM)
- Connectors — Web crawler, Google Drive, WhatsApp/Chat sync (MEDIUM)
- Container Configuration: Allows setting and retrieving container-level settings, such as filter prompts, to customize ingestion pipelines. This is managed via dedicated API endpoints.
- 🔒 Data sovereignty — Self-hosted, your data stays yours
- 🔍 Graph transparency — Full visibility into the knowledge graph
- ✅ Validation Protocol v3.0 — 8 quality filters (vs. black-box approaches)
- 💰 ~$20/month estimated operational cost
See docs/SPEC.md for the complete development specification.
Private — All rights reserved.