Decentralized storage has always faced a longstanding challenge—once data is uploaded to the chain, it's done; but when you actually need to use it, it becomes a problem. Storage itself isn't difficult, but subsequent processing is a hassle. Massive amounts of unstructured data pile up in distributed networks, lacking effective query mechanisms, and no one helps you organize tags and metadata. In the end, this data is like being frozen—becoming "sleeping assets." To retrieve anything, you must remember hash values or index addresses. Fuzzy searches? Don't even think about it. Developers face an even worse situation—they have to manually add tags and supplement metadata for each file, which is time-consuming, labor-intensive, and prone to inconsistency. This "data silo" phenomenon directly stifles the application potential of decentralized storage in AI, social, content platforms, and other scenarios.

The good news is that some people are starting to break the deadlock. In early 2026, blockchain AI smart platform Zark Lab and Walrus Protocol achieved a major breakthrough—adding an AI intelligent layer directly to Walrus's storage network, completely changing the way data interaction works. Those "static files" were instantly upgraded to "intelligent resources," and the data value was immediately activated.

The key to this collaboration is AI-driven automated data structuring. Zark Lab developed a dedicated AI publishing system for Walrus that can automatically process all uploaded files without human intervention throughout the entire process. Text files? AI automatically extracts keywords, core ideas, and topic classifications. Image files? Recognize scenes, objects, colors, and other visual features, and automatically generate tags. Audio and video files are not left out—automatic processing includes audio transcription, content analysis, and video frame recognition. As a result, unstructured data instantly gains machine-readable intelligent attributes, truly unlocking the value of stored data.