Strac
Sensitive data discovery software
Cloud data security software
Data-centric security software
Data loss prevention (DLP) software
Cloud security software
Data security software
Data security posture management (DSPM)
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What is Strac
Strac is a cloud-based data loss prevention (DLP) and sensitive data discovery product focused on identifying and reducing exposure of regulated data in SaaS applications and cloud collaboration tools. It is used by security and compliance teams to scan content, detect sensitive data types, and apply remediation actions such as redaction, quarantine, deletion, or policy-based alerts. The product emphasizes pre-built integrations for common SaaS services and automated workflows to reduce manual review. It also supports compliance-oriented reporting for audits and internal governance.
Broad SaaS integration coverage
Strac focuses on scanning and controlling sensitive data in widely used SaaS apps (for example, collaboration, ticketing, and messaging platforms). This makes it practical for organizations that have most business data outside traditional endpoints and file servers. Pre-built connectors reduce the need for custom ingestion pipelines compared with more data-platform-centric approaches.
Automated remediation workflows
The product supports actions such as redaction, deletion, quarantine, and alerting when policies match sensitive content. This helps teams move from discovery to enforcement without building separate automation. It is well-suited to operational DLP use cases where rapid containment matters.
Compliance-oriented detection and reporting
Strac includes detection for common regulated data types (for example, PII/PHI/PCI patterns) and provides reporting aligned to compliance needs. This supports audit preparation and ongoing governance for cloud collaboration environments. The emphasis on policy outcomes (find, alert, remediate) fits security operations workflows.
Depth varies by connector
Capabilities can differ across SaaS integrations depending on each platform’s APIs and event models. Some services may support richer remediation (for example, redaction) while others may be limited to alerting or tagging. Buyers typically need to validate per-connector coverage for their highest-risk systems.
Limited data governance breadth
Compared with platforms that combine privacy operations, records management, and broader data governance workflows, Strac is more narrowly centered on DLP-style discovery and enforcement. Organizations seeking end-to-end privacy request handling, consent management, or enterprise-wide governance may need additional tools. This can increase overall program complexity.
Advanced classification may require tuning
Pattern-based and rules-driven detection can require tuning to reduce false positives and to handle business-specific sensitive data. Teams with complex data models may need to invest time in custom dictionaries, exceptions, and policy testing. This is common in DLP deployments but should be planned for in rollout timelines.
Seller details
Strac, Inc.
Unsure
Private
https://www.strac.io/
https://x.com/strac_io
https://www.linkedin.com/company/strac/
