CEII and IP, caught as drawings.
It reads meaning beyond text, so critical infrastructure information and IP get caught as diagrams, models, and coordinates, not just prose.
Inside discovery and classification →ENERGY
Secuvy learns your data itself, so drawings, well logs, and sensor histories get classified by meaning, not by matching office-document patterns.
THE CEILING
Your AI wants sensor histories, drawings, and survey data, and that is also the data that maps your infrastructure and holds your IP.
58% of IT leaders call classifying data for AI their hardest technical problem.
Pattern rules were written for office documents. A one-line diagram, a well log, or a turbine's sensor history matches none of them, so it goes unclassified.
What nobody can classify, nobody can tag for use.
THE SHIFT
Secuvy learns your data itself, unsupervised and in place, reading how files relate, repeat, and take shape, not just what their text says.
It recommends a classification. Your team confirms it, and the engine learns your operation a little better each time.
No format is unfamiliar for long.
What non-pattern classification means →FOR ENERGY TEAMS
It reads meaning beyond text, so critical infrastructure information and IP get caught as diagrams, models, and coordinates, not just prose.
Inside discovery and classification →Your engineers confirm Secuvy's recommendations instead of cataloging files by hand, and the queue shrinks as the engine learns the operation.
Why the engine learns →A Data Bill of Materials records what fed each model and what was held out, ready for auditors and regulators.
The DBOM in depth →MEETS YOUR BAR
Thirty minutes on your own environment. Bring your OT security lead.
Book a demo →PLAIN ANSWERS
It connects read-only and recommends; nothing is installed on operational systems, and files never move or change.
Yes. It reads how files relate, repeat, and take shape, so diagrams, models, and logs get classified by meaning.
Yes. Secuvy classifies data in place across operational and enterprise sources, so files stay in their existing systems and workflows. Teams get a shared view of sensitivity and policy without moving the underlying data into one repository.
Yes. A Data Bill of Materials records every model's inputs, what was held out, and when each entry changed.
Confidently fuel every AI pipeline.