Memori
Open-source memory engine for LLM apps and agents that need persistent context injection.
Memori overview
Memori is an open-source memory engine from GibsonAI for giving LLM applications and agents persistent memory, context injection, and configurable recall behavior.
Focused memory engine
Memori centers on memory behavior rather than broad workflow orchestration.
A focused engine is easier to embed into existing applications.Persistent context injection
The docs describe memory concepts for injecting relevant context into interactions.
Agents become more useful when recall happens at the right moment.Apache-2.0 open-source release
Public materials describe Memori as Apache-2.0 open source.
Permissive licensing helps teams experiment without early legal friction.When to use Memori
Conversational memory
Remember preferences and prior facts across user conversations.
Agent task context
Inject previous task details when an agent resumes work.
Memory library evaluation
Compare a focused memory engine against heavier agent platforms.
How it compares
Use Memori when you want memory inside an existing app rather than adopting a whole agent runtime.
Questions
What should I check before using Memori?
Test Memori with repeated sessions. Add facts, update them, ask for recall, inspect retrieval behavior, and verify deletion or scoping controls before storing sensitive user or project memory.
Is Memori open source?
Memori is listed with Apache-2.0 based on the official source links in this profile. Re-check the repository, model card, or docs before production use.
Who should evaluate Memori?
Memori is most worth evaluating for developers adding memory to LLM applications.