AI Data Classification: Bruce Power cuts 15 Million Files to 3 Million

Company Background

Bruce Power is one of the largest and most innovative nuclear-generating stations in the world. With over 10,000 employees and contractors, it generates a third of Ontario’s power.

The Challenge

Bruce Power faced an end-of-life scenario in 2015. The company secured approval to operate until 2064, but ran on a 20-year-old enterprise asset management system.

Jay Hitchcock, Director of the Digital Transformation Office, inherited the problem. Nobody could classify what the organization held. Legacy systems could not process the incoming data volumes or meet workforce expectations for information retrieval.

The team refused to settle for the status quo.

The Solution

Bruce Power started by acknowledging what it did not know.

Shinydocs crawled every structured and unstructured repository and classified each file in place. Classification surfaced data lapses, permission inconsistencies, and addressable flaws across the estate. Bruce Power finally understood what it held.

Classification separated the valuable from the disposable. Redundant, obsolete, and trivial files were identified and routed to remediation. Documents containing personally identifiable information, company IP, and security details were flagged and handled appropriately.

That classified content then powered Search across the organization. Staff found information in seconds instead of hours. Hundreds of terabytes of digital and legacy content became searchable, with existing permissions enforced on every result.

Departments made faster supply chain and operational decisions. Classification turned Bruce Power's dark data into an asset the whole organization could use. This private AI data classification approach supports enterprise search across regulated industries, utilities, and large corporations.