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Description

EverOS is a memory and skills infrastructure platform built to give AI agents persistent context across sessions, tools, and deployment environments. Before an agent makes a model call, EverOS retrieves relevant memories and supplies the context needed for the current task without requiring the full history to remain in the prompt window. Its memory engine is designed for low-latency retrieval and supports persistent context across multiple agents and platforms. EverOS also provides self-evolving procedural memory through a system that records completed tasks as cases and consolidates repeated successful patterns into reusable skills. These skills can be shared across an agent team so useful behaviors improve over time without requiring every workflow to be manually hardcoded. The platform supports multimodal ingestion for PDFs, images, documents, spreadsheets, slides, Markdown files, and URLs through a unified workflow. EverOS integrates with Claude Code, Codex, OpenClaw, Hermes, MCP servers, and software built against OpenAI- or Anthropic-compatible interfaces. Developers can use EverOS Cloud or run the open source Apache 2.0 stack on their own infrastructure while keeping memories portable through Markdown export. EverOS is intended for AI application developers, agent platform teams, and enterprises that need durable memory, cross-agent knowledge sharing, and efficient context retrieval.

Description

Humatron serves as a comprehensive AI workforce platform, transforming AI agents into secure and trusted digital workers that seamlessly integrate with various teams, tools, and business processes. Organizations have the ability to construct, recruit, tailor, train, oversee, and regulate these AI workers from a unified control dashboard, treating them more like digital personnel rather than mere assistants. Each AI worker can leverage advanced core agents, such as Claude, OpenAI, Manus, OpenClaw, Hermes, Cursor, or bespoke agent systems, which grants businesses the flexibility to interchange or update underlying models without altering the workforce layer. These AI workers are capable of operating independently, initiating and completing tasks, collaborating with team members, acquiring new skills, and communicating through established platforms like email, Slack, Teams, Zoom, and phone. The platform allows for the creation of builds that define reusable tools, rules, behaviors, and agent integrations, while each individual worker operates as a distinct instance tailored to meet the specific needs of a company, team, and role. This level of customization ensures that businesses can optimize their AI workforce to align perfectly with their operational goals.