Document ML System Architecture 
APRIL 23, 2025
Traditional keyword-based search mechanisms are often insufficient for locating relevant documents efficiently, requiring extensive manual review to extract meaningful insights. This solution improves the findability and accessibility of archival records by automating metadata enrichment, document classification, and summarization.
AWS Machine Learning Blog
DECEMBER 4, 2024
Businesses are under pressure to show return on investment (ROI) from AI use cases, whether predictive machine learning (ML) or generative AI. Only 54% of ML prototypes make it to production, and only 5% of generative AI use cases make it to production. Using SageMaker, you can build, train and deploy ML models.
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AWS Machine Learning Blog
OCTOBER 14, 2024
For many of these use cases, businesses are building Retrieval Augmented Generation (RAG) style chat-based assistants, where a powerful LLM can reference company-specific documents to answer questions relevant to a particular business or use case. Generate a grounded response to the original question based on the retrieved documents.
AWS Machine Learning Blog
NOVEMBER 26, 2024
Challenges in deploying advanced ML models in healthcare Rad AI, being an AI-first company, integrates machine learning (ML) models across various functions—from product development to customer success, from novel research to internal applications. Rad AI’s ML organization tackles this challenge on two fronts.
AWS Machine Learning Blog
MARCH 10, 2025
The traditional approach of manually sifting through countless research documents, industry reports, and financial statements is not only time-consuming but can also lead to missed opportunities and incomplete analysis. This event-driven architecture provides immediate processing of new documents.
O'Reilly Media
NOVEMBER 19, 2024
Here’s a simple rough sketch of RAG: Start with a collection of documents about a domain. Split each document into chunks. One more embellishment is to use a graph neural network (GNN) trained on the documents. Chunk your documents from unstructured data sources, as usual in GraphRAG. at Facebook—both from 2020.
AWS Machine Learning Blog
FEBRUARY 13, 2025
For this demo, weve implemented metadata filtering to retrieve only the appropriate level of documents based on the users access level, further enhancing efficiency and security. To understand how this dynamic role-based functionality works under the hood, lets examine the following system architecture diagram.
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