Proof vs. EverOS

EverOS

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What is Proof?

Proof is a collaborative document editing platform that enables seamless cooperation between human users and AI agents. It offers teams a cohesive workspace where both AI and human participants can contribute by writing, suggesting edits, commenting, and tracking contributions. Each contributor's authorship is clearly indicated through a color-coded gutter, making it easy for users to distinguish between human-written text and AI-generated content. Changes made by the AI appear as suggestions, akin to the track changes functionality, allowing users to review and decide on each modification on an individual basis. Furthermore, AI agents can leave comments on specific parts of the document to offer clarifications, ask questions, raise issues, or participate in discussions right within the text. Users can easily create documents and share links with a variety of agents, including Claude Code, ChatGPT, Codex, or OpenClaw, fostering collaboration in a shared environment instead of dealing with .md file exchanges. Proof caters to a diverse array of applications, such as bug reports, product requirement outlines, implementation plans, research summaries, growth analytics, content assessments, strategic initiatives, memos, and proposals. This cutting-edge tool is especially advantageous for teams aiming to improve their collaborative workflows while ensuring clear attribution and effective feedback channels. Overall, Proof stands out as a transformative resource in the realm of document collaboration, blending human creativity with AI efficiency.

What is EverOS?

EverOS is a persistent memory platform for AI agents that combines long-term context, multimodal ingestion, self-evolving skills, and cross-platform compatibility. The system is designed to sit inside an existing agent loop and retrieve relevant context before each large language model call. Rather than sending an entire conversation or knowledge history into the model every time, EverOS selects the most relevant stored memories for the current task. Its memory architecture is built to support low-latency retrieval while reducing token usage and maintaining continuity across sessions. EverOS also introduces self-evolving skills, which turn successful task executions into cases that can later be consolidated into reusable procedural knowledge. Repeated successful patterns can be promoted into shared skills that are available to multiple agents without requiring manual curation or brittle workflow logic. The platform accepts multimodal sources including PDFs, images, spreadsheets, documents, slides, URLs, and Markdown and automatically parses, chunks, and indexes them for retrieval. EverOS works with agent environments and interfaces such as Claude Code, Codex, OpenClaw, Hermes, MCP, and OpenAI- and Anthropic-compatible SDKs. Its Markdown-first portability model allows organizations to export memories in a readable, version-controllable format and move between hosted and self-managed deployments. Teams can start with EverOS Cloud or deploy the Apache 2.0 open source version on their own infrastructure using the same API and memory format. EverOS is designed for developers, AI infrastructure teams, and enterprises that want agents to retain context, learn reusable procedures, and operate more efficiently across tools and environments.