Build an AI-powered document processing platform with open source NER model and LLM on Amazon SageMaker
Machine Learning Blog
This article describes an AI-powered document processing platform developed for a U.S. National Laboratory using Amazon SageMaker, designed to improve archival data accessibility and management.
- Uses Mixtral-8x7B LLM and BERT-based NER model for document analysis
- Implements a serverless, cost-optimized architecture with dynamic SageMaker endpoints
- Processes documents through multiple stages:
- Extractive summarization
- Title generation
- Abstractive summarization
- Author extraction
- Can process 100,000 documents in 12 hours
- Reduces processing costs by 75-90% through initial extractive summarization
The solution offers a flexible, modular approach to automated document processing, demonstrating the potential of AI and machine learning in managing large-scale archival data.
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