EverMind
Add persistent context to an agent project
EverMind presents a family of AI memory products, including EverOS for agent memory and EverMe as a personal memory hub. This overview focuses on EverOS, the infrastructure described on the main site, rather than assuming that each family member has the same features or access model.
The vendor describes maintaining context across days, sessions and platforms. Its stated use cases include multi-agent coordination, organizational knowledge and customer-support history. These describe intended applications for a memory layer; they do not establish the behavior of a particular agent connected to it.
Ingest different kinds of material
EverOS describes multimodal retrieval and ingestion through its mRAG approach. The listed inputs include PDFs, images, Word documents, spreadsheets, presentations and URLs, alongside text and other material. The vendor says this information can be parsed and stored through one API for later retrieval.
The page also describes recording agent trajectories as Cases and turning recurring patterns into reusable Skills. That is the documented mechanism behind its self-evolving-memory offering, rather than a claim that an agent automatically learns the right lesson from every task.
Inspect stored memories and skills
The Memory Bank interface exposes user, group and agent memories for inspection and management. The description also includes editing generated Skills. These controls are relevant to examine if a workflow will retain information that can later affect an agent's answers or actions.
EverMind publishes benchmark scores and comparisons on the homepage. This entry does not reproduce those experiments, adopt its claims of infinite scaling or make a latency prediction for your project. Evaluate retrieval and correction behavior using the information your own workflow needs.
Choose managed or self-hosted deployment
EverOS is offered through a managed cloud service and an open-source deployment route. The cloud description includes scaling, maintenance and enterprise support. The self-hosted route describes running the memory stack on your own infrastructure and inspecting its layers.
The homepage lists an installation sequence with a standalone demo, initialization and a first memory added and retrieved. Read the deployment material linked from the official site before choosing a route; this entry does not supply unverified setup commands or pricing. No memory service was deployed, and no model or ingestion API was called.