You bought the GPUs. You hired the ML team. And your AI project is still stalled. Not because the science is hard, but because no one can find and assemble the data to train on. In life sciences, the real bottleneck isn’t compute. It’s data readiness. Here’s why the right datasets go dark, and how to bring them back into reach.
The bottleneck in AI drug discovery isn’t compute. It’s locating the relevant data. →
Snowflake Horizon Catalog governs every table, app, and model — but 80% of enterprise data still lives in files it never mapped. Diskover indexes the unstructured estate across every storage tier and delivers it into Snowflake as queryable rows: metadata first, content on demand. One catalog, from tables to files.
Diskover CPO Paul Honrud, a 35-year data management veteran, explains why managing unstructured data is an ongoing discipline, not a one-time cleanup. Ignored files pile up until storage fills, workflows slow, and risk climbs. See how a ‘lifestyle’ approach keeps data optimized and AI-ready.
Why good data management is a lifestyle, not a cleanup project. →
AI success depends less on models and GPUs than on the data behind them, and over 80% of enterprise data is unstructured. See the five-step process, from discovery to governance, that turns messy files into clean, discoverable, AI-ready data your models can actually use.
Unstructured data preparation for AI: Why it matters for the model. →
Most enterprises racing toward AI aren’t ready, and the problem isn’t a lack of data. It’s visibility, structure, and control over sprawling unstructured estates. See the six most common blockers, from data silos to cold data on costly tiers, and where to start fixing each.
Is your data AI-ready? Most enterprises aren’t—here’s why. →
For oil and gas teams, seismic and subsurface data sprawls across on-prem, cloud, and aging archives. See how GeoComputing’s RiVA platform and Diskover unite it into one searchable view, with fast metadata discovery and automated curation that make geoscience data trustworthy and AI-ready.
Unlocking the power of unstructured data with Diskover on the RiVA platform. →
When Diskover partnered with Snowflake, an early priority was clear: stream unstructured file metadata and storage analytics straight into Snowflake at scale. See how the team built that pipeline, the trade-offs they weighed, and what it means for preparing enterprise data for AI.
From whiteboard to workflow: How Diskover built its Openflow Connector for Snowflake. →
Diskover VP of Product Olivier Rivard shares how Anthropic’s Model Context Protocol turned AI from a productivity tool into a true development partner, one that connects to real systems, pulls live data, and acts. It’s the story of moving from experiments to real products for unstructured data management.
How MCP turned AI experiments into real product ideas. →
Most enterprises want AI but lack AI-ready data foundations, especially for unstructured data. See how Diskover acts as a super connector, indexing storage everywhere, building a searchable metadata catalog, then curating and moving the right data into Snowflake for analytics and AI pipelines.
Boost the value of AI-ready unstructured data with Diskover + Snowflake. →
Unstructured data has long been treated as digital junk, kept for backup or compliance. But it’s the hidden fuel of next-generation AI. Using the semiconductor industry as a lens, see how discovery, enrichment, and automation turn dormant files into a genuine source of innovation.
From files to fuel: Rethinking unstructured data for the AI era. →
