| Best fit | Enterprise AI and data teams governing which data is appropriate for AI workloads. | Security teams prioritizing data access, exposure, threat detection, and remediation. | Start with the operating decision: AI input governance or permissions-centric security. |
|---|
| Classification | Self-learning classification of pattern and non-pattern data using content, context, and relationships. | Contextual classification with out-of-the-box classifiers, policies, and Microsoft Purview integration. | Both classify sensitive data. Secuvy centers non-pattern data and AI use-case appropriateness. |
|---|
| AI evidence | A DBOM records pipeline inputs, exclusions, sensitivity, status, policy reason, and destination. | Atlas provides AI inventory, risk, governance, audit trails, and runtime controls. | Secuvy centers evidence about the source data used by each AI pipeline. |
|---|
| Permissions | Maps data to users, applications, sensitivity, and use. | An access graph analyzes entitlements, group membership, sharing links, and permissions, with automated remediation. | Varonis has the stronger documented permissions-remediation workflow. |
|---|
| Data handling | Classifies files where they live without moving or changing production files. | Covers cloud, SaaS, and on-premises data through SaaS integrations and private collectors. | Both support distributed enterprise environments through different operating models. |
|---|
| Integrations | Secuvy reports support for more than 250 data sources. | Broad cloud, SaaS, on-premises, and Microsoft Purview coverage. | Validate connector scope against the data estate in the proof of value. |
|---|
| Pricing | Quote-based. No public list price was found on the current pages reviewed. | Quote-based, licensed by user count, with a 30-day unlimited trial. | Obtain matched quotes for the same sources, users, modules, and services. |
|---|