AppSec Prot-On vs Secuvy Data Discovery & Classification: Side-by-Side Comparison (2026)

AppSec Prot-On: Information Rights Management solution for document classification & protection. built by APPSEC CONSULTING. Core capabilities include Automatic information classification and labeling, Protection for PDF, Office, text, video, audio, and photo files, Policy-based access control enforcement..

Secuvy Data Discovery & Classification: AI-driven data discovery & classification using unsupervised learning. built by Secuvy. Core capabilities include Unsupervised machine learning-based data classification that self-trains without requiring pre-labeled datasets, Data linkage to connect records across different formats and systems for improved classification accuracy, Detection of complex and organization-specific data types including CUI, ITAR, IP, CAD files, and confidential documents..

Both serve the Data Classification market but differ in approach, feature depth, and target audience.

AppSec Prot-On differentiates with Automatic information classification and labeling, Protection for PDF, Office, text, video, audio, and photo files, Policy-based access control enforcement. Secuvy Data Discovery & Classification differentiates with Unsupervised machine learning-based data classification that self-trains without requiring pre-labeled datasets, Data linkage to connect records across different formats and systems for improved classification accuracy, Detection of complex and organization-specific data types including CUI, ITAR, IP, CAD files, and confidential documents.

AppSec Prot-On is developed by APPSEC CONSULTING. Secuvy Data Discovery & Classification is developed by Secuvy. Vendor maturity, funding stage, and team size can be important factors when evaluating long-term viability and support quality.

AppSec Prot-On and Secuvy Data Discovery & Classification serve similar Data Classification use cases: both are Data Classification tools. Review the feature comparison above to determine which fits your requirements.