ai

AI natural language interfaces are redefining how we interact with data. Instead of navigating complex dashboards or waiting on reports, users can simply ask questions and get instant insights. As unstructured data grows and AI fluency spreads, natural language is becoming the new interface for discovery—bridging the gap between human understanding and machine intelligence.

The CloudSoda AI Data Assistant began as an experiment with Anthropic’s Model Context Protocol (MCP) and quickly became a working prototype unveiled at the NAB Show. Built to analyze storage, simulate cost savings, and surface duplicates, it gave both engineers and executives instant, actionable answers in plain language.

Diskover VP of Product Olivier Rivard shares how Anthropic’s Model Context Protocol (MCP) transformed his AI experiments into real product ideas — and what it means for the future of unstructured data management.

Unstructured data is one of the biggest barriers to AI adoption. This post explores why it’s so hard to work with—and how Diskover and Snowflake are partnering to make it AI-ready.

Most organizations still think of unstructured data as digital clutter—PDFs, videos, logs, and scattered files. But in the AI era, this data is far more than storage overhead—it’s fuel. Fuel for breakthrough chip design, scientific simulations, and next-gen AI workflows. In this blog, we explore how shifting your mindset—and your data strategy—can turn unstructured data into a powerful engine for innovation.