Training Data Risk
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Identify PII, PHI, credentials, and IP in training datasets
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Surface bias, drift, and regulatory violations before they’re baked into the model
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Map lineage from raw data to model outputs to support explainability
BigID delivers visibility, context, and control for AI risk across your enterprise:
Identify PII, PHI, credentials, and IP in training datasets
Surface bias, drift, and regulatory violations before they’re baked into the model
Map lineage from raw data to model outputs to support explainability
Detect unauthorized AI tool usage (e.g. unsanctioned copilots, chatbots)
Prevent sensitive data from being ingested, processed, or surfaced by GenAI models
Discover when sensitive info is being shared via Slack, email, or code
See who has access to AI data, models, and pipelines
Enforce least privilege and zero trust controls for users and workloads
Detect excessive permissions or toxic access combinations
Align AI data practices with frameworks like the EU AI Act, GDPR, CPRA, and NIST AI RMF
Automate privacy impact assessments and AI risk evaluations
Identify where AI violates data minimization, purpose limitation, or residency requirements
Monitor how sensitive data flows into and out of AI systems
Detect when confidential or toxic data is unintentionally exposed or misused
Trigger automated remediation: redact, revoke, quarantine, or delete
Understand how sensitive data impacts model behavior, predictions, and output
Map training data lineage to improve explainability and traceability
Support audit readiness and regulatory response with detailed visibility into what data shaped your models
Discover, govern, and reduce AI risk - before it becomes exposure.