Polymer DSPM

Polymer DSPM Overview

Polymer DSPM is a real-time data security posture management platform built for the AI era, focused on identifying, analyzing, and mitigating security risks in real time across SaaS ecosystems and AI workflows. Through intelligent data discovery and automated policy enforcement, it helps enterprises protect sensitive data in environments where AI adoption is widespread. It is particularly well suited to healthcare, financial services, and organizations that must meet SOC 2, HIPAA, and CCPA/GDPR compliance requirements.

Key Features

• Real-time data discovery and classification: Combines NLP and RegEx to detect 50+ sensitive data types across 40+ languages
• AI security protection: A unique SecureRAG feature protects retrieval-augmented generation pipelines and monitors LLM interactions
• Automated policy enforcement: Real-time violation remediation via data redaction, access revocation, and custom workflows
• Identity-aware detection and response: Creates context-driven security policies for both human and AI identities
• Continuous compliance monitoring: Generates audit logs aligned with major frameworks (HIPAA, SOC 2, CCPA, GDPR)
• Human risk management: Brings employees into the security perimeter through real-time alerts and contextual training

Use Cases

In AI-enabled workplaces, security teams use Polymer to monitor employee interactions with AI tools such as ChatGPT and Copilot, ensuring sensitive customer data is not fed into AI model training. For cloud collaboration platforms (Slack, Teams, Google Workspace), enterprises use the platform to detect file over-sharing and unauthorized AI app usage, and to block data leaks automatically the instant a violation occurs.

Unique Advantages

Compared with traditional DLP tools, Polymer evolves from "data loss prevention" to "real-time data protection," emphasizing proactive action over passive alerting. Among DSPM platforms, its positioning in AI workflow security is forward-looking: it developed native features like SecureRAG and prompt monitoring early in the generative AI wave. Its cloud-first architecture enables 15-minute deployment, far faster than traditional agent-based models.