Poly: The Intelligent Cloud File Browser

What

Poly is an AI-powered cloud file browser available on web and desktop. It is designed to help people store, browse, research, organize, and work with files by understanding file contents in detail, including pages, paragraphs, scenes, and visual elements.

The product appears suited to knowledge workers, researchers, creative teams, and anyone managing large or mixed-format file collections. Its core workflow combines file storage, natural-language and content-based search, in-file analysis, summarization, sharing, and collaboration, positioning it somewhere between a file manager, knowledge workspace, and AI-assisted content retrieval tool.

Features

• Content-aware search across many file types — Poly lets users search by image, concept, phrase, color, face, and more, helping them locate files based on meaning and visual characteristics rather than only filenames.
• In-file retrieval — It can search within files for an exact page, scene, or clip, which is useful when teams need specific moments or sections inside long documents, videos, or media archives.
• Conversational file research — Users can ask questions about their files, such as locating source footage or transcribing an interview clip, making file discovery and analysis more direct.
• Broad file format support — The page lists support for formats including audio, images, documents, video, code, archives, and design files, which makes it relevant for mixed-content repositories.
• Organization and collaboration controls — Shared drives, public sharing, version history, flexible views, and file properties support structured teamwork and file governance within the workspace.
• Privacy, offline access, and AI visibility controls — Poly states that files are encrypted on device, in transit, and in the cloud, supports offline web and desktop use, and includes a “Hide from AI” option for files users do not want read by the agent.

Helpful Tips

• Evaluate search quality on real repositories — For this category of product, the main differentiator is how well semantic and in-file search work on your actual documents, media, and naming conventions.
• Define file visibility rules early — Features like shared drives, public sharing, and “Hide from AI” are most useful when teams establish clear policies for sensitive, public, and AI-readable content.
• Use it where mixed media causes retrieval friction — Products like Poly are likely most valuable for teams handling combinations of documents, video, images, audio, and design assets rather than simple folder storage alone.
• Test desktop and offline workflows — If local file access and intermittent connectivity matter, confirm how desktop sync and offline editing behave in day-to-day use before wider rollout.
• Treat coming-soon collaboration features cautiously — The page mentions collaborative conversations as coming soon, so buyers should distinguish between current capabilities and roadmap items.

OpenClaw Skills

Poly could likely complement the OpenClaw ecosystem as a file-centric knowledge layer for agents that need to search, inspect, summarize, and organize unstructured content. A likely workflow would be an OpenClaw agent that monitors a project folder, identifies new research files or media, generates structured notes, tags assets by topic or visual similarity, and routes outputs into downstream team workflows. The page does not describe a native OpenClaw integration, so this should be treated as a likely use case rather than a confirmed capability.

For target users such as researchers, creative operations teams, archivists, or media production staff, the combination could support skills like archive librarian agents, interview transcription and extraction agents, technical document review agents, and visual reference pack builders. In practice, that could shift work from manual folder navigation toward agent-assisted retrieval and synthesis, especially in environments where teams need to move quickly across large, heterogeneous file collections.