Use case

Cyera for Safe and Secure AI Use

Enable AI Adoption While Keeping Your Data Secure. Discover, isolate, and sanitize sensitive data to ensure that it is only accessible to authorized AI Copilots and large language models (LLMs).

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AI Adoption is Transformative. Cyera Makes It Safer

AI offers immense potential, but it also presents new risks around data security, privacy, and compliance. Organizations must ensure that sensitive data is protected and that AI systems don’t inadvertently expose, ingest, or misuse information. With Cyera, you gain greater visibility into the data used for AI initiatives. 

80%

of businesses are either exploring or implementing AI solutions

55%

of companies listed data privacy and security as top AI implementation challenges

$15.7T

expected AI-driven addition to the global economy by 2030

Find and Classify Data for AI Use

Accelerate AI readiness with rapid data discovery, by identifying sensitive data before it enters AI models or tools.

Automatically classify data types for secure AI use, such as personal information, financial records, or intellectual property

Gain context about data residency, retention, and protection measures to help prevent unintended exposure or compliance concerns when using AI

Assign correct sensitivity labels to help ensure AI tools like Microsoft Copilot use the right data

Assess AI Data Risks

Understand the potential risks associated with using company data within critical AI projects.

Identify high-risk data that should not be fed into AI models and tools to reduce your risk

Assign correct sensitivity labels to help ensure AI tools like Microsoft Copilot use the right data

Detect potential compliance violations, overly permissive or unauthorized access, introduced by using sensitive data in AI systems, such as LLMs or Copilots

Continuously Monitor AI Data Issues

Maintain oversight of your data by continuously assessing risks, and tracking changes related to the data used by AI systems.

Protect against insider threats by discovering identities, and by assigning trust levels based on context like: MFA on or off, Internal or external user, unusual activity, and more

Monitor data compliance and AI risks with pre-built policies to automatically flag critical issues

Detect and correct misaligned Microsoft sensitivity labels to protect data from entering Microsoft Copilot or AI models