Archiledger Knowledge Graph

Example Use Cases

• 1

  A persistent memory bank to store user preferences, decisions, and context across conversations.

• 2

  Analyze and document codebases or document corpora into structured, linked knowledge graphs.

• 3

  Semantic search and graph traversal capabilities to retrieve and explore connected knowledge.

Description

Archiledger is a specialized knowledge graph system designed as a Retrieval-Augmented Generation (RAG) tool that enables LLM assistants to store, connect, and recall information persistently using a graph database. It supports atomic notes linked by typed relationships, semantic vector search, and tagging for rich context and connected thinking. The server is optimized for local development and personal use, providing infrastructure to build AI assistants with persistent memory and knowledge graph capabilities.