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Accelerating insurance policy reviews with generative AI: Verisk’s Mozart companion

Flipboard

Along with each document slice, we store the metadata associated with it using an internal Metadata API, which provides document characteristics like document type, jurisdiction, version number, and effective dates. This process has been implemented as a periodic job to keep the vector database updated with new documents.

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How Vericast optimized feature engineering using Amazon SageMaker Processing

AWS Machine Learning Blog

Monitoring metadata and output When the job starts, a Lambda function writes the job processing metadata (the current job configuration and other log information) into the DynamoDB log table. This metadata and log information maintains a history of the job, its initial and ongoing configuration, and other important data.