EverMind

EverMind provides an open-source memory infrastructure called EverOS designed to give AI agents continuous, self-evolving memory that persists across sessions, days, and platforms. Unlike standard large language models (LLMs) that start each conversation from scratch, EverOS introduces a dedicated memory layer that enables agents to retain context, build on past interactions, and evolve their understanding over time. This addresses a fundamental limitation of current LLMs: context windows that max out at 128K–200K tokens, causing agents to forget earlier information and forcing users to repeat themselves. Traditional retrieval-augmented generation (RAG) systems can fetch similar text chunks but lack deep comprehension of the user’s history and intent. EverOS goes beyond simple retrieval by maintaining a long-term identity for each agent and allowing it to remember facts, preferences, and conversation threads indefinitely. The system is benchmarked against three major evaluation suites. On LoCoMo (Long Context Modeling) it achieves 93.05% accuracy, on LongMemEval it reaches 83.00%, and on HaluMem (Hallucination in Memory)