Master Cyera Data Loss Prevention with our step-by-step tutorial, detailed feature walkthrough, and expert tips.
Explore the key features that make Cyera Data Loss Prevention powerful for data security workflows.
Cyera replaces the rule-based, signature-driven approach of legacy DLP with an AI-native engine that uses machine learning and large language models for classification. Where legacy tools require months of rule tuning and dedicated administrators, Cyera ships pre-built policies and pre-analyzed alerts so deployment can happen in minutes. The platform is also agentless, removing the endpoint installation overhead that has historically made DLP rollouts painful. Cyera positions this as enabling a 3-person team to deliver the output of a traditional 30-person DLP operation.
Cyera does not publish pricing on its website and operates on an enterprise sales model â interested buyers must request a demo through cyera.com/demo to receive a quote. Pricing typically scales with data volume, number of cloud accounts and SaaS connectors, and which platform modules are licensed (DSPM, DLP, AI security, etc.). Compared to enterprise DLP competitors in our directory, this opaque pricing is standard for the Data Security category but can slow evaluation for mid-market buyers. Expect costs in the five- to six-figure annual range based on typical enterprise DSPM/DLP deals.
Cyera supports both cloud and on-premises environments according to its product positioning, making it suitable for hybrid enterprises. However, the platform is architecturally cloud-first and uses agentless connectors to discover and classify data across AWS, Azure, GCP, and major SaaS applications. On-prem coverage is available but organizations with primarily air-gapped or legacy on-prem data estates may find the cloud-native design less optimized for their environment than purpose-built on-prem DLP tools.
Cyera's AI-driven classification engine identifies a broad range of sensitive data including PII (names, SSNs, addresses), PHI (medical records and identifiers), PCI data (payment card information), financial records, intellectual property, and source code. Because the engine uses large language models rather than regex alone, it can identify context-dependent sensitive data â for example, distinguishing a customer record from a test fixture. This supports compliance with GDPR, HIPAA, PCI-DSS, and emerging AI governance frameworks.
Cyera's DLP is designed to address modern data loss vectors including generative AI usage, where employees may paste sensitive data into LLMs. The platform monitors data in motion across browsers, endpoints, and email to detect and block sensitive data flows into unauthorized AI tools. Combined with Cyera's broader AI security capabilities, organizations can both discover where AI is being used and prevent regulated data from leaking into third-party models. The February 2025 partnership with Abnormal AI further strengthens coverage of AI-driven attack vectors.
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Tutorial updated March 2026