Most teams are being asked to put enterprise data in front of AI agents without knowing what that data contains, who owns it, or who can reach it. In this live session, we start with a data estate that looks ordinary (file shares, databases, a stray JSON export) and run Everpure Data Intelligence against it in real time. You'll watch discovery, classification, and context build up on screen, including the moment a single innocuous file turns into thousands of regulated data elements. Then we close the loop: label at the source, trigger a policy action, and let an AI assistant ask the estate which data is safe to use.
Key takeaways:
- Discovery at the source: How Everpure Data Intelligence connects to structured, unstructured, cloud, on-prem, and mainframe sources and classifies content in place, without moving or copying data
- Classification to context: What the knowledge graph adds beyond a sensitivity tag (owner, access, relationships, policy) and why that's what AI needs to trust a dataset
- Metadata-only triage: How the new Everpure Data Intelligence File Edition surfaces age, freshness, and ownership signals across shares before any content scan
- Intelligence to action: Writing labels back to native metadata, triggering alerts and workflows, and querying findings in plain language
ashduong
Updated 3 hours ago