Accelerate performance using a custom chunking mechanism with Amazon Bedrock

This article discusses how Accenture used Amazon Bedrock's Knowledge Bases to create a custom chunking mechanism to enhance performance when extracting structured information from unstructured PDF documents containing tables, images, and text formatted in various styles.

Specifically, the article covers:

• The importance of proper chunking for chatbots and NLP applications to maintain context and avoid hallucinations
• How Accenture implemented a custom chunking mechanism using Amazon Textract, chunking text based on PDF layout elements like paragraphs, tables, and chapter titles
• Benefits of custom chunking like context preservation, flexible chunk sizes, improved retrieval performance, and seamless AWS integration
• Performance comparison showing improved accuracy using custom chunking and metadata filtering compared to fixed chunking
• How to clean up AWS resources like OpenSearch Service, S3 bucket, and Lambda functions after implementing the solution