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Strac Data Security

AI-native data security platform for DLP, DSPM, and data governance across SaaS

Data Protection
Commercial
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Strac Data Security Description

Strac Data Security is a data protection platform that provides data discovery, classification, and loss prevention capabilities across SaaS applications, cloud environments, generative AI tools, and endpoints. The platform scans for and identifies sensitive data including PII, PHI, PCI data, source code, and intellectual property. The solution offers Data Security Posture Management (DSPM) functionality to discover and classify sensitive data across connected systems. It includes Data Loss Prevention (DLP) capabilities that can automatically detect and remediate sensitive information in real-time across communication channels, collaboration tools, and file storage systems. Strac provides AI data governance features to control sensitive data exposure in generative AI platforms like ChatGPT, Copilot, Gemini, and Claude. The platform supports endpoint protection for Mac and Linux systems to prevent data leakage from devices. The platform integrates with various SaaS applications through no-code integrations that can be deployed in approximately 15 minutes. Remediation actions include automatic redaction of sensitive data from messages, emails, documents, and attachments. The solution uses machine learning for data classification and detection. Strac offers tokenization and proxy API capabilities to implement zero-data architecture, allowing organizations to avoid storing sensitive data on backend servers. The platform supports compliance requirements for PCI, HIPAA, SOC 2, ISO 27001, and GDPR.

Strac Data Security FAQ

Common questions about Strac Data Security including features, pricing, alternatives, and user reviews.

Strac Data Security is AI-native data security platform for DLP, DSPM, and data governance across SaaS developed by Strac. It is a Data Protection solution designed to help security teams with AI Security, Compliance, Data Classification.

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