Use cases
Where a memory layer earns its place.
Memorg is a small library you drop next to an LLM app. These are the scenarios teams reach for it most — each with the concrete features it leans on.
Conversation continuity for LLM chat
App builders shipping LLM chat
Keep a chat coherent across turns, sessions, and days without stuffing the whole history into every prompt.
Read the use case →Upgrade naive RAG to structured recall
RAG teams who outgrew nearest-neighbour search
Move past a bare vector store to retrieval that understands users, sessions, recency, and importance.
Read the use case →A memory layer for your agent
Teams with an existing agent loop
Drop deterministic recall next to any orchestrator without adopting a whole agent runtime.
Read the use case →Support bots that remember the customer
Teams building support and assistant bots
Give a support assistant per-customer recall so it stops asking for context the customer already gave.
Read the use case →Notes and documents as memory
Builders who need more than chat recall
Store documents, notes, and arbitrary items alongside conversations and search across them.
Read the use case →Have a different shape in mind?
Memorg is library-first — it drops next to almost any LLM stack. Tell us what you're building.