EverOS
EverOS is a persistent memory infrastructure platform for AI agents that provides long-term, multimodal, cross-platform context across agent workflows. The system retrieves relevant memories before model calls, allowing agents to reuse prior context without repeatedly loading large histories into the prompt window. EverOS also includes self-evolving skills, which capture successful execution trajectories as cases and promote recurring patterns into reusable procedural knowledge. The platform can ingest PDFs, images, documents, spreadsheets, slides, Markdown, and URLs and convert them into searchable memory for inference-time retrieval. It supports cloud and self-hosted deployment, exports memories in Markdown, and integrates with tools such as Claude Code, Codex, OpenClaw, Hermes, MCP, and OpenAI- or Anthropic-compatible SDKs. EverOS achieves 93.05% on the LoCoMo long-term memory benchmark (research: arXiv:2601.02163).
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Cognee
Cognee is an open source AI memory engine that transforms raw data into structured knowledge graphs, enhancing the accuracy and contextual understanding of AI agents. It supports various data types, including unstructured text, media files, PDFs, and tables, and integrates seamlessly with several data sources. Cognee employs modular ECL pipelines to process and organize data, enabling AI agents to retrieve relevant information efficiently. It is compatible with vector and graph databases and supports LLM frameworks like OpenAI, LlamaIndex, and LangChain. Key features include customizable storage options, RDF-based ontologies for smart data structuring, and the ability to run on-premises, ensuring data privacy and compliance. Cognee's distributed system is scalable, capable of handling large volumes of data, and is designed to reduce AI hallucinations by providing AI agents with a coherent and interconnected data landscape.
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Membase
Membase is a long-term memory service for people and developers building AI agents. It brings information from conversations, files, web pages and connected apps into a persistent memory that users can review, correct, delete and export. A web app and Chrome extension let users manage memories, save browser content and share selected information with supported AI tools. Developers connect custom agents through MCP, the REST API, command-line interface, or Python and TypeScript SDKs. Separate memories and access controls support personal, project and client contexts, with controls to grant or revoke access. The hosted service stores and processes source content to build and retrieve memory.
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Agno
Agno is a lightweight framework for building agents with memory, knowledge, tools, and reasoning. Developers use Agno to build reasoning agents, multimodal agents, teams of agents, and agentic workflows. Agno also provides a beautiful UI to chat with agents and tools to monitor and evaluate their performance. It is model-agnostic, providing a unified interface to over 23 model providers, with no lock-in. Agents instantiate in approximately 2μs on average (10,000x faster than LangGraph) and use about 3.75KiB memory on average (50x less than LangGraph). Agno supports reasoning as a first-class citizen, allowing agents to "think" and "analyze" using reasoning models, ReasoningTools, or a custom CoT+Tool-use approach. Agents are natively multimodal and capable of processing text, image, audio, and video inputs and outputs. The framework offers an advanced multi-agent architecture with three modes, route, collaborate, and coordinate.
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