Memori
Memori is agent-native memory infrastructure. A LLM-agnostic layer that turns agent execution and conversation into structured, persistent state for production systems. Built for enterprise, Memori works with the data infrastructure you already run, no rip-and-replace, and deploys across managed cloud, single-tenant cloud, VPC, and on-premises.
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Memori is an LLM-agnostic memory layer that converts agent execution and conversation into structured, persistent state. It is positioned for enterprise production systems, integrating with existing data infrastructure and supporting managed cloud, single-tenant cloud, VPC, and on-premises deployment.
You reach for it when your agents need durable, structured memory across sessions without replacing your current data stack.
Use it to
- Persist agent conversation state across sessions
- Structure agent execution history for production use
- Deploy memory infrastructure on-prem or in a VPC
- Give LLM-agnostic agents shared memory state
- Add long- and short-term memory to agentic workflows
For Teams building production, enterprise-grade agentic applications
- Role
- agent-app
- Language
- Python
- Licence
- custom (licence file present)
- Forks
- 3,464
- Open issues
- 14
- Last push
- 2026-09-03
- Latest release
- v1.0.0 · 2025-08-04