Today's AI is a genius without a past. We give it a memory. At EverMind, we empower every agent and application with a near-infinite context, enabling a continuous self that grows with every interaction. This is the foundation for an AI that truly understands you, acts with long-term consistency, and evolves with greater proactivity.
EverMemOS is the core memory operating system designed to give AI a lasting identity. It moves beyond simple data retrieval, acting as a "memory application processor" that enables AI to reason with context, grow with experience, and evolve from a stateless tool into a true, personalized partner . With a state-of-the-art score of 92.3 on LoCoMo, EverMemOS is the open-source foundation for the next era of intelligent agents.
EverMemBench is the first end-to-end benchmark evaluating the closed loop of "memory retrieval - memory awareness", with three main tasks—long-term conversations, causal attribution, and passive memory.
EverMemModel is the Core Engine for Parametric Long-Context Understanding. Its ultimate goal is to achieve near-infinite context length. Unlike traditional RAG systems, it stores memory data using the language model's KV cache and supports end-to-end training.
Using a unified, production-grade evaluation framework, we benchmarked leading memory systems — EverMemOS, Mem0, MemOS, Zep, and MemU — under the same datasets, metrics, and answer model. This framework provides a fair, transparent, and reproducible standard for evaluating real-world memory performance in the Agentic Era. And EverMemOS delivered best-in-class results across LoCoMo and LongMemEval.
Part of the EverMemModel modules, the ReRankModel achieves SOTA performance on 2wiki and Hotpotqa.
The EverMemModel has achieved SOTA performance both on retrieval task and QA task.
