Polymer vs Strac: Data Loss Prevention Comparison (2026)
Polymer offers a transparent, per-user per-month per-integration pricing model, while Strac requires a scoping call for pricing. Polymer lists more detailed policy management features and reporting, whereas Strac emphasizes its detection, remediation, discovery, and classification capabilities for sensitive data. Strac provides a specific list of integrations, while Polymer states "Integration with external systems" more generally.
AI Citation Scorecard
How often each is cited by major AI engines when buyers ask data loss prevention questions. Last 90 days across ChatGPT, Perplexity, Gemini, Claude, and Copilot.
Probes run hourly; each (engine × query) combo retests every ~3 days.
Pricing
Key Features
- ✓Multiple policies
- ✓Policy customization
- ✓Unlimited entities & rules
- ✓Single tenancy hosting
- ✓Standard processing
- ✓Activity monitoring
- ✓Training, enforcement, & audit
- ✓Advanced reporting
- ✓Detects & remediates sensitive data
- ✓Discovers & classifies sensitive data
When to choose Polymer
Polymer is suitable for organizations seeking a DLP solution with clear, per-user per-month per-integration pricing and features like multiple policies, policy customization, unlimited entities and rules, single tenancy hosting, standard processing, activity monitoring, training, enforcement, audit, and advanced reporting.
When to choose Strac
Strac is suitable for organizations that prioritize agentless deployment, require detection and remediation of sensitive data across specific platforms like Slack, Google Workspace, Microsoft 365, ChatGPT, Claude, Salesforce, Zendesk, and GitHub, and prefer to receive a customized quote based on their specific scope.
Frequently Asked Questions
AI visibility profiles
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