Data classification is the practice of identifying information and labelling it by sensitivity — for example Public, Internal or Confidential — so that people, DLP and compliance controls can treat each file appropriately.
The layer everything depends on
Without labels, DLP guesses, audits become archaeology, and privacy requests turn into manual searches. Classification turns an undifferentiated sea of files into governed information a policy can act on.
Three ways to label
Manual classification lets users apply the right label as they create content. Automatic classification applies labels by policy — keywords, patterns, fingerprints. AI classification reads content and suggests or applies labels at scale, even across a legacy backlog.
Labels that travel
Siberson Veriket writes persistent metadata plus visual markings, so the label follows the file across systems and is readable by DLP, SIEM and discovery — making every downstream control more accurate.