An OS-inspired memory layer for personalized AI agents that organizes user memory into short-, mid-, and long-term tiers and migrates entries between them. Published as an EMNLP 2025 Oral.
- Storage
- Segmented-page storage with a heat-based updating mechanism that promotes/demotes memory across short / mid / long-term tiers.
- Retrieval
- Retrieves relevant user and assistant memory across the tiered store to condition responses; details per the paper and repo.
- Self-host
- Self-host: moderate
- License
- Apache-2.0
- Pricing
- Open source (Apache-2.0), free to self-host · Free / OSS
- GitHub stars
- 1,487
- Last release
- 2025-07-18
- Last commit
- 2026-04-28
- First catalogued
- 2026-06-28
Strengths
- Peer-reviewed (EMNLP 2025 Oral)
- OS-style tiered memory with heat-based promotion/demotion
- Permissive Apache-2.0 license
Watch out
- Name collides with the separate MemTensor MemOS project — they are different systems
- Last repo push ~April 2026; maintenance cadence is research-project-paced
Best for
- Personalized conversational agents needing tiered long-term user memory
Benchmark results
No sourced results yet.
Sources
- https://github.com/BAI-LAB/MemoryOS (vendor)
- https://arxiv.org/abs/2506.06326 (paper)
Last verified 2026-06-28 · updated by manual-refresh