Cerebra
Memory architecture that's alive. Stores, retrieves, and — most importantly — understands the depth and meaning of what it holds.
Overview
Cerebra is a memory architecture that goes beyond storage and retrieval. It understands the relational context between what it holds and surfaces meaning, not just matches. The result is a globally accessible memory layer that any module in your stack can read from or write to under your control.
Dogfooded by LumaWeave for graph-level memory and by agents that need deep, persistent context, Cerebra turns one-shot prompts into ongoing conversations and short-lived workflows into compounding intelligence.
Bleeding-edge storage and retrieval methods sit underneath a clean interface. You decide what gets remembered, what gets surfaced, and what gets forgotten — Cerebra handles the rest.
Key concepts
- Bleeding-edge storage and retrieval methods
- Understands relational context between stored memories
- Globally accessible within the stack — you control reads and writes
- Dogfood memory directly into agents' active context windows
- Memory maps, insight feeds, embeddings, timelines, and activity views
- Built to amplify any agent it touches