AI Data Lineage - Training & Runtime
Continuously track data lineage across training and runtime, linking source data, transformations, and model outputs with end-to-end data journeys that map training and runtime data across pipelines, APIs, and models while providing regulator-ready lineage evidence.
Get a demoWhy is AI-specific data lineage better than traditional tracking?
End-to-End Data Journeys
Maps training and runtime data across pipelines, APIs, and models with complete visibility from source to inference.
Lineage-Aware Detection
Flags gaps, shadow flows, or policy violations in real-time throughout the AI lifecycle with continuous monitoring.
Immutable Audit Trails
Provides regulator-ready lineage evidence linked to lawful basis and obligations for defensible AI compliance.
Training-Runtime Bridge
Connects training data provenance to runtime inference decisions for complete AI accountability and explainability.
How does AI data lineage work from training to runtime?
Identifies all training and runtime datasets across pipelines, SaaS, and storage. Ingests metadata about source, schema, and transformations with continuous scanning. Learn more about AI data lineage fundamentals.
Builds lineage graphs that connect inputs, preprocessing steps, and outputs. Detects gaps, shadow data, or untracked flows with real-time monitoring. Read more about Data Journeys breakthrough technology.
Governs lineage with ownership, lawful basis, and retention tags. Enforces policy requirements across datasets and pipelines with automated controls. Learn about AI governance examples and lessons learned.
Generates audit-ready lineage reports that map directly to GDPR, AI Act, and sectoral requirements. Proves lawful use with linked evidence and compliance validation. Discover EU AI Act compliance requirements.
Flags lineage gaps or violations (e.g., unapproved data used in training). Provides remediation workflows for engineering and compliance teams with automated task routing. Learn about data flow monitoring best practices.
What business value does AI data lineage provide?
Complete Data Transparency
Show exactly how data is used in training and runtime with comprehensive lineage graphs and transformation tracking.
Faster Incident Response
Pinpoint affected datasets and transformations instantly when issues arise, enabling rapid containment and remediation across AI systems.
Defensible Compliance
Provide proof of lawful AI use to regulators and customers with immutable audit trails and regulator-ready documentation.
The complete picture of your data in motion
Ditch legacy tools that miss the action with continuous tracking that follows data flows from source code to AI models, predicting and preventing violations in real-time. Learn about Data Journeys capabilities.
"AI is creating and moving data faster than any team can track. Only AI-native tools like Relyance can keep up with the discovery and enforcement loop."
"With Relyance AI, we established enhanced visibility of data processing activities, seeing an impressive increase of 1,660% within three weeks of deployment."
FAQ
What is AI data lineage for training and runtime?
AI data lineage for training and runtime continuously tracks how data flows through machine learning systems from initial training datasets through model inference in production. It maps complete data transformations, feature engineering, and inference decisions to provide end-to-end visibility and accountability for AI systems. Learn more about AI data lineage tracking.
How does AI lineage differ from traditional data lineage?
AI lineage tracks complex data transformations unique to machine learning, including feature engineering, model training processes, inference decisions, and derived attributes that traditional lineage tools cannot capture. It provides real-time monitoring of AI-specific data flows and connects training data provenance to runtime decisions for complete AI accountability. Discover modern AI data lineage approaches.
What makes lineage-aware detection critical for AI systems?
Lineage-aware detection identifies unauthorized data usage, policy violations, and compliance gaps specific to AI workflows in real-time, such as unapproved training data or shadow AI models. This prevents AI-specific risks like bias propagation, consent violations, and regulatory non-compliance before they impact production systems. Read about AI governance best practices.
How quickly can AI lineage violations be detected and resolved?
AI lineage violations are detected in real-time through continuous monitoring of training pipelines and runtime inference flows. The system immediately flags issues like unauthorized data usage or policy violations, then routes remediation tasks to appropriate teams with complete context for rapid resolution.
Which AI compliance frameworks does lineage tracking support?
AI data lineage tracking supports comprehensive compliance with EU AI Act, GDPR, CCPA, HIPAA, and sectoral AI regulations by providing audit-ready documentation of data usage, transformation tracking, and lawful basis validation throughout the AI lifecycle. Explore data lineage governance capabilities.
