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Orchestrate an intelligent document processing workflow using tools in Amazon Bedrock

AWS Machine Learning

In this post, we focus on one such complex workflow: document processing. Rule-based systems or specialized machine learning (ML) models often struggle with the variability of real-world documents, especially when dealing with semi-structured and unstructured data.

APIs 84
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Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning

It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. API Gateway is serverless and hence automatically scales with traffic. API Gateway also provides a WebSocket API. Incoming requests to the gateway go through this point.

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Track LLM model evaluation using Amazon SageMaker managed MLflow and FMEval

AWS Machine Learning

By documenting the specific model versions, fine-tuning parameters, and prompt engineering techniques employed, teams can better understand the factors contributing to their AI systems performance. Evaluation algorithm Computes evaluation metrics to model outputs. Different algorithms have different metrics to be specified.

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Evaluate RAG responses with Amazon Bedrock, LlamaIndex and RAGAS

AWS Machine Learning

Current RAG pipelines frequently employ similarity-based metrics such as ROUGE , BLEU , and BERTScore to assess the quality of the generated responses, which is essential for refining and enhancing the models capabilities. More sophisticated metrics are needed to evaluate factual alignment and accuracy.

Metrics 94
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Empower your generative AI application with a comprehensive custom observability solution

AWS Machine Learning

Observability refers to the ability to understand the internal state and behavior of a system by analyzing its outputs, logs, and metrics. For a detailed breakdown of the features and implementation specifics, refer to the comprehensive documentation in the GitHub repository.

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Customize Amazon Textract with business-specific documents using Custom Queries

AWS Machine Learning

Amazon Textract is a machine learning (ML) service that automatically extracts text, handwriting, and data from scanned documents. Queries is a feature that enables you to extract specific pieces of information from varying, complex documents using natural language. personal or cashier’s checks), financial institution and country (e.g.,

APIs 124
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Principal Financial Group uses QnABot on AWS and Amazon Q Business to enhance workforce productivity with generative AI

AWS Machine Learning

Principal wanted to use existing internal FAQs, documentation, and unstructured data and build an intelligent chatbot that could provide quick access to the right information for different roles. Model monitoring of key NLP metrics was incorporated and controls were implemented to prevent unsafe, unethical, or off-topic responses.

Chatbots 115