EverMemOS

EverMind builds memory infrastructure for AI agents. Its purpose is to let an assistant hold context across days, sessions and platforms rather than starting from zero whenever a conversation runs past the model context window, and to let agents build on what happened before instead of asking users to repeat themselves. The product family is EverOS, a memory layer for agents, and EverMe, a personal memory tool that assembles a visual digital twin from a user's past, both built on a long term memory system the company calls EverCore. EverOS ingests and retrieves across formats including PDFs, images and spreadsheets, records agent task histories as Cases, distills recurring patterns from those into reusable Skills, and exposes a Memory Bank where user, group and agent memories can be inspected and edited directly. The company argues that retrieval alone is not enough, since similar text chunks carry no comprehension, and that memory also has to track how facts change over time and be shared across coordinating agents rather than a single chatbot. It publishes benchmark results of 93.05 percent on LoCoMo, 83.00 percent on LongMemEval and 93.04 percent on HaluMem, and says those benchmarks are open source and reproducible by anyone. EverOS can be self hosted. An open source deployment under the Apache 2.0 license runs the full memory stack on your own infrastructure, with the code published on GitHub. A managed EverOS Cloud Service adds hosting, automatic scaling and enterprise support. No prices are published for either, and the pricing URL returns a not found error, so the cloud service is priced through sign up or a sales conversation. EverMemOS, the name this entry is listed under, appears on the site as a research paper on memory for long horizon reasoning rather than as a shipping product.