Teams with an existing agent loop

A memory layer for your agent

Drop deterministic recall next to any orchestrator without adopting a whole agent runtime.

In short

Memorg is just the memory layer — it does not run your agent loop, own your prompts, or ship a planner. You keep your orchestrator and call Memorg when the agent needs to remember or recall.

The problem

✕Agent runtimes bundle memory with a whole framework you may not want to adopt.
✕You already have a loop, tools, and prompts you like — you only need the recall piece.
✕You want retrieval you can reason about, not an agent silently deciding what to read.

With Memorg

✓Use Memorg as a library from inside your existing loop.
✓Write exchanges and typed memory items as the agent works; retrieve before it acts.
✓Ranking is deterministic, so agent behaviour stays debuggable and reproducible.

How it works

1

Keep your orchestrator

Memorg does not replace your agent framework — it sits beside it as a plain library call.
2

Write memory as the agent runs

Persist exchanges and memory items (notes, documents) with tags at the right hierarchy level.
3

Recall before each action

Call search_context() to fetch scoped, budget-trimmed context ahead of the next tool call or generation.