AI Document 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
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.
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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. This post is cowritten with Isaac Cameron and Alex Gnibus from Tecton.
AWS Machine Learning Blog
NOVEMBER 26, 2024
This post is co-written with Ken Kao and Hasan Ali Demirci from Rad AI. Rad AI has reshaped radiology reporting, developing solutions that streamline the most tedious and repetitive tasks, and saving radiologists’ time. In this post, we share how Rad AI reduced real-time inference latency by 50% using Amazon SageMaker.
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. These operational inefficiencies meant that we had to revisit our solution architecture.
AssemblyAI
NOVEMBER 19, 2024
In a world where data is a crucial asset for training AI models, we've seen firsthand at AssemblyAI how properly managing this vital resource is essential in making progress toward our goal of democratizing state-of-the-art Speech AI. That's where our AI Lakehouse comes in. High-Level Architecture Diagram Figure 1.
O'Reilly Media
NOVEMBER 19, 2024
One popular term encountered in generative AI practice is retrieval-augmented generation (RAG). 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.
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