Category: Best Practices

This post is a joint collaboration between Salesforce and AWS and is being cross-published on both the Salesforce Engineering Blog and the AWS Machine Learning Blog. The Salesforce AI Model Serving team is working to push the boundaries of natural language processing and AI capabilities for enterprise applications. Their key focus areas include optimizing large […]

The collaboration between Clario and AWS demonstrated the potential of AWS AI and machine learning (AI/ML) services and generative AI models, such as Anthropic’s Claude, to streamline document generation processes in the life sciences industry and, specifically, for complicated clinical trial processes.

In this post, we demonstrate how to elevate business productivity by leveraging Amazon Q to provide insights that enable research, data analysis, and report potential fraud cases within Amazon Connect.

This post demonstrates how enterprises can implement a scalable agentic text-to-SQL solution using Amazon Bedrock Agents, with advanced error-handling tools and automated schema discovery to enhance database query efficiency.

Organizations are increasingly using multiple large language models (LLMs) when building generative AI applications. Although an individual LLM can be highly capable, it might not optimally address a wide range of use cases or meet diverse performance requirements. The multi-LLM approach enables organizations to effectively choose the right model for each task, adapt to different […]

This post demonstrates how Amazon Bedrock Knowledge Bases can help you scale your data management effectively while maintaining proper access controls on different management levels.

In this blog, we discuss how to optimize prompting in Amazon Nova for the best price-performance.

Lumi is a leading Australian fintech lender empowering small businesses with fast, flexible, and transparent funding solutions. They use real-time data and machine learning (ML) to offer customized loans that fuel sustainable growth and solve the challenges of accessing capital. This post explores how Lumi uses Amazon SageMaker AI to meet this goal, enhance their transaction processing and classification capabilities, and ultimately grow their business by providing faster processing of loan applications, more accurate credit decisions, and improved customer experience.

To improve factual accuracy of large language model (LLM) responses, AWS announced Amazon Bedrock Automated Reasoning checks (in gated preview) at AWS re:Invent 2024. In this post, we discuss how to help prevent generative AI hallucinations using Amazon Bedrock Automated Reasoning checks.

In this post, we discuss how to evaluate the performance of your knowledge base, including the metrics and data to use for evaluation. We also address some of the tactics and configuration changes that can improve specific metrics.