AI compliance regulations, such as the EU AI Act and sectoral laws, require organizations to map how personal data moves from source systems into AI models and back to business decisions. This data lineage is critical for Article 13 (Transparency), Article 14 (Record-Keeping), and for fulfilling Data Subject Access Requests (DSARs) related to automated decisions. Manual mapping across data lakes, feature stores, and model registries is slow and error-prone. An AI integration connects to your data governance platform (e.g., Collibra, Alation, Microsoft Purview) and your AI/ML stack (e.g., Databricks MLflow, SageMaker, Vertex AI) to automatically discover and link these flows. The integration typically uses the platform's REST APIs to ingest metadata, then applies LLMs to infer relationships, classify data types (e.g., special category data under GDPR), and generate plain-English summaries of data journeys.




