Category: HAQM Bedrock

This post explores deploying a text-to-SQL pipeline using generative AI models and HAQM Bedrock to ask natural language questions to a genomics database. We demonstrate how to implement an AI assistant web interface with AWS Amplify and explain the prompt engineering strategies adopted to generate the SQL queries. Finally, we present instructions to deploy the service in your own AWS account.

We are excited to announce the availability of Gemma 3 27B Instruct models through HAQM Bedrock Marketplace and HAQM SageMaker JumpStart. In this post, we show you how to get started with Gemma 3 27B Instruct on both HAQM Bedrock Marketplace and SageMaker JumpStart, and how to use the model’s powerful instruction-following capabilities in your applications.

In this post, we walk through building a full-stack application that processes multimodal content using HAQM Bedrock Data Automation, stores the extracted information in an HAQM Bedrock knowledge base, and enables natural language querying through a RAG-based Q&A interface.

In this post, we show you how to implement and evaluate three powerful techniques for tailoring FMs to your business needs: RAG, fine-tuning, and a hybrid approach combining both methods. We provid ready-to-use code to help you experiment with these approaches and make informed decisions based on your specific use case and dataset.

HAQM Bedrock Data Automation helps organizations streamline development and boost efficiency through customizable, multimodal analytics. It eliminates the heavy lifting of unstructured content processing at scale, whether for video or audio. The new capabilities make it faster to extract tailored, generative AI-powered insights like scene summaries, key topics, and customer intents from video and audio. This unlocks the value of unstructured content for use cases such as improving sales productivity and enhancing customer experience.

In this post, we share how GuardianGamer uses AWS services including HAQM Nova and HAQM Bedrock to deliver a scalable and efficient supervision platform. The team uses HAQM Nova for intelligent narrative generation to provide parents with meaningful insights into their children’s gaming activities and social interactions, while maintaining a non-intrusive approach to monitoring.

This post demonstrates how HAQM Bedrock, combined with a user feedback dataset and few-shot prompting, can refine responses for higher user satisfaction. By using HAQM Titan Text Embeddings v2, we demonstrate a statistically significant improvement in response quality, making it a valuable tool for applications seeking accurate and personalized responses.

In this post, we present a solution to incorporate HAQM Bedrock Agents in your Slack workspace. We guide you through configuring a Slack workspace, deploying integration components in HAQM Web Services, and using this solution.

In this post, we present a solution for securing distributed logging multi-account deployments using HAQM Bedrock and LangChain.

In this post, we introduce a multi-agent collaboration pipeline for processing unstructured insurance data using HAQM Bedrock, featuring specialized agents for classification, conversion, and metadata extraction. We demonstrate how this domain-aware approach transforms diverse data formats like claims documents, videos, and audio files into metadata-rich outputs that enable fraud detection, customer 360-degree views, and advanced analytics.