Getting Started
Getting Started
Get started with Magneteco memory infrastructure
Getting Started
Magneteco provides persistent memory infrastructure for AI agents. This guide will help you integrate Magneteco into your application.
Overview
Magneteco works by:
- Ingesting content - Conversations and events are sent to Magneteco
- Extracting facts - LLM extracts atomic facts and entities
- Building knowledge - Facts are stored with embeddings and relationships
- Retrieving context - Query memory to get relevant context for your agent
Memory Layers
| Layer | Purpose | Storage |
|---|---|---|
| Resources | Raw immutable logs | S3 |
| Items | Atomic extracted facts | PostgreSQL + pgvector |
| Categories | Evolving summaries | PostgreSQL |
| Graph | Entity relationships | Neo4j |
Architecture Overview
┌─────────────────────────────────────────────────────────────────┐
│ YOUR APPS │
├─────────────┬─────────────┬─────────────┬───────────────────────┤
│ App A │ App B │ App C │ Future Apps │
└──────┬──────┴──────┬──────┴──────┬──────┴─────────┬─────────────┘
│ │ │ │
└─────────────┴─────────────┴────────────────┘
│
▼
┌─────────────────────────────┐
│ MAGNETECO SERVICE │
│ │
│ • Memorize (conversations) │
│ • Events (system events) │
│ • Webhooks (external) │
│ • Retrieve (queries) │
│ • Tools (agent interface) │
└─────────────┬───────────────┘
│
┌────────────────────┼────────────────────┐
│ │ │
▼ ▼ ▼
PostgreSQL Neo4j S3
+ pgvector (graph) (raw logs)