Document Natural Language Processing 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.
O'Reilly Media
NOVEMBER 19, 2024
See the primary sources “ REALM: Retrieval-Augmented Language Model Pre-Training ” by Kelvin Guu, et al., 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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AWS Machine Learning Blog
MARCH 10, 2025
Investment professionals face the mounting challenge of processing vast amounts of data to make timely, informed decisions. 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.
AWS Machine Learning Blog
MARCH 31, 2023
You configure curated answers to frequently asked questions using an integrated content management system that supports rich text and rich voice responses optimized for each channel. You can expand the solution’s knowledge base to include searching existing documents and webpage content using Amazon Kendra.
AWS Machine Learning Blog
FEBRUARY 19, 2025
To use Automated Reasoning checks, you first create an Automated Reasoning policy by encoding a set of logical rules and variables from available source documentation. Automated Reasoning checks deliver deterministic verification of model outputs against documented rules, complete with audit trails and mathematical proof of policy adherence.
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