AI models rely on features sourced from tables that lack proper documentation, ownership, and data quality visibility. This increases operational and regulatory risk.
There is no clear view of which PII, financial data, or protected attributes flow into training pipelines, making risk exposure difficult to assess.
Feature engineering workflows evolve quickly, creating undocumented changes that introduce drift and quietly degrade model performance.
When regulators or internal auditors ask for evidence that prohibited data sources aren’t used, teams struggle to provide clear, traceable documentation.
Connect Dataedo to data warehouses, feature stores, and batch/stream sources. Organize training datasets under subject areas like Customer Risk or Fraud Detection.
Use the Data Catalog and Business Glossary to define model inputs in clear, business-friendly terms. Capture definitions, calculation logic, and quality notes so both technical and non-technical stakeholders understand exactly what each dataset represents and how it’s used in AI models.
Use Data Lineage to trace raw source tables through preprocessing, feature engineering, and model retraining workflows. Create a clear, visual map of how data flows into AI models to support transparency, impact analysis, and audit readiness.
Apply classification tags to mark PII, financial data, or protected attributes in training features. Document masking rules and exclusion decisions.
Provide auditors with a full view of your AI ecosystem by showing exactly which data feeds and inputs each model uses, ensuring complete transparency and traceability.
Avoid unexpected outcomes by monitoring upstream data changes and guaranteeing that every model performs consistently.
Accelerate your compliance workflows by generating detailed, up-to-date documentation directly from your live model catalog, reducing manual effort and review cycles.
Define and document model features in clear business language, including definitions, calculation rules, and quality notes, so your team and auditors understand exactly what each input represents.
Trace every feature from raw source tables through feature engineering and model training workflows, giving you a complete, end-to-end view of how data flows into your AI models.
Identify and label PII, financial data, or protected attributes in model inputs, including masking rules and exclusion decisions, to ensure your AI models comply with privacy and regulatory requirements.
Founder
Explore Dataedo through a preconfigured data catalog with sample data, try it with your own data during a 14-day free trial, or book a demo.