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Version: 2.15.0

AI Model Data Integrity and Traceability

Scenario​

An organization needs to ensure the integrity and traceability of data throughout the lifecycle of AI models, from collection to deployment, while complying with regulatory standards.

Implementation​

Data is stored securely with restricted access. Data preprocessing and integrity checks verify that data remains unchanged. Any modifications are logged in the chain of custody record (database). Data used for training AI models can be tracked, protected, and snapshotted.

Outcome​

The solution maintains data integrity and traceability throughout the AI project lifecycle, ensures regulatory compliance, and provides transparent and accountable data handling practices, leading to high-quality and trustworthy AI models.

See also​