memU
Open-source agentic memory layer for AI companions and applications.
What is memU?
MemU is an open-source agentic memory layer designed specifically for LLM applications and AI companions. It functions as an intelligent, interconnected file system that automatically organizes, connects, and evolves user memories. If you are wondering what is MemU and how about MemU (agent memory)?, it is essentially a highly efficient framework built to provide conversational AI, autonomous memory management, and deep integration with a custom knowledge graph. Compared to traditional vector storage setups like MemU vs Memos, it delivers significantly higher accuracy and faster retrieval at a lower cost, achieving a stellar 92.09% average accuracy on the Locomo dataset benchmark across all complex reasoning tasks.
Category
Best memU use cases by task, role, industry, and platform
These use cases show where memU fits best, ranked by fit score before popularity or pricing.
memU Pricing Plans
Compare memU free options, memU paid pricing plans, and usage notes before you choose the best way to use this AI tool in 2026.
Free, Professional from $29/mo
Perfect for getting started. Up to 30 memory calls, basic retrieval, community support, and API access.
For growing teams and applications. Up to 600 memory calls, advanced retrieval algorithms, priority support, advanced analytics, and custom integrations. Includes a 14-day free trial.
For large-scale deployments. Unlimited memory calls, dedicated infrastructure, 24/7 dedicated support, custom SLA, on-premise deployment, and custom training.
Pricing updated:Jun 12, 2026
memU AI Features
memU Pros and Cons
Pros
- Open-source and highly flexible framework
- Significantly higher accuracy and faster retrieval speeds
- Multi-platform integration with major LLM providers
- Cost-effective memory infrastructure for enterprise scaling
Limitations
- Several ecosystem integrations (like SillyTavern, CrewAI, N8N) are still listed as coming soon
- Free tier is restricted to 30 memory calls per month