You build an Azure AI Search skillset that runs OCR, key phrase extraction, and a custom entity skill over a large collection of scanned contracts. Beyond serving a searchable index, your data science team wants the enriched, structured output (extracted entities and key phrases per document) persisted to Azure Blob Storage as tables and objects so they can run separate downstream analytics in Azure Machine Learning without re-invoking the skillset. What should you configure in the indexer/skillset to meet this requirement?