RichmondAlake/memorizz

Official code for the paper "Memora: A Harmonic Memory Representation Balancing Abstraction and Specificity"

Self-evolving memory OS for LLM & AI Agents: ultra-persistent memory, hybrid-retrieval, and cross-task skill reuse, with 35.24% token savings and DeepSeek Harness support.

One portable memory layer for every AI agent: local-first, Markdown-native, user-owned, and self-evolving across apps, tools, and workflows.

[EMNLP 2025 Oral] MemoryOS is designed to provide a memory operating system for personalized AI agents.

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.

30 sec to give your AI agents persistent memory. Reduce 90% token consumption while also maintaining quality.

A plain-text memory system for AI agents. Clone it, point your agent at it, start remembering.

Universal memory layer for AI Agents. It provides scalable, extensible, and interoperable memory storage and retrieval to streamline AI agent state management for next-generation autonomous systems.