AWS Machine Learning Blog

Category: Customer Solutions

Transforming credit decisions using generative AI with Rich Data Co and AWS

The mission of Rich Data Co (RDC) is to broaden access to sustainable credit globally. Its software-as-a-service (SaaS) solution empowers leading banks and lenders with deep customer insights and AI-driven decision-making capabilities. In this post, we discuss how RDC uses generative AI on Amazon Bedrock to build these assistants and accelerate its overall mission of democratizing access to sustainable credit.

Architecture diagram showing the end-to-end workflow for Crop.photo’s automated bulk image editing using AWS services.

Automate bulk image editing with Crop.photo and Amazon Rekognition

In this post, we explore how Crop.photo uses Amazon Rekognition to provide sophisticated image analysis, enabling automated and precise editing of large volumes of images. This integration streamlines the image editing process for clients, providing speed and accuracy, which is crucial in the fast-paced environments of ecommerce and sports.

Appian Architecture diagram

Revolutionizing business processes with Amazon Bedrock and Appian’s generative AI skills

AWS and Appian’s collaboration marks a significant advancement in business process automation. By using the power of Amazon Bedrock and Anthropic’s Claude models, Appian empowers enterprises to optimize and automate processes for greater efficiency and effectiveness. This blog post will cover how Appian AI skills build automation into organizations’ mission-critical processes to improve operational excellence, reduce costs, and build scalable solutions.

Building the future of construction analytics: CONXAI’s AI inference on Amazon EKS

CONXAI Technology GmbH is pioneering the development of an advanced AI platform for the Architecture, Engineering, and Construction (AEC) industry. In this post, we dive deep into how CONXAI hosts the state-of-the-art OneFormer segmentation model on AWS using Amazon Simple Storage Service (Amazon S3), Amazon Elastic Kubernetes Service (Amazon EKS), KServe, and NVIDIA Triton.

Architecture Diagram

How Untold Studios empowers artists with an AI assistant built on Amazon Bedrock

Untold Studios is a tech-driven, leading creative studio specializing in high-end visual effects and animation. This post details how we used Amazon Bedrock to create an AI assistant (Untold Assistant), providing artists with a straightforward way to access our internal resources through a natural language interface integrated directly into their existing Slack workflow.

OfferUp improved local results by 54% and relevance recall by 27% with multimodal search on Amazon Bedrock and Amazon OpenSearch Service

In this post, we demonstrate how OfferUp transformed its foundational search architecture using Amazon Titan Multimodal Embeddings and OpenSearch Service, significantly increasing user engagement, improving search quality and offering users the ability to search with both text and images. OfferUp selected Amazon Titan Multimodal Embeddings and Amazon OpenSearch Service for their fully managed capabilities, enabling the development of a robust multimodal search solution with high accuracy and a faster time to market for search and recommendation use cases.

Accelerate video Q&A workflows using Amazon Bedrock Knowledge Bases, Amazon Transcribe, and thoughtful UX design

The solution presented in this post demonstrates a powerful pattern for accelerating video and audio review workflows while maintaining human oversight. By combining the power of AI models in Amazon Bedrock with human expertise, you can create tools that not only boost productivity but also maintain the critical element of human judgment in important decision-making processes.

Boost team innovation, productivity, and knowledge sharing with Amazon Q Apps

In this post, we demonstrate how Amazon Q Apps can help maximize the value of existing knowledge resources and improve productivity among various teams, ranging from finance to DevOps to support engineers. We share specific examples of how the generative AI assistant can enable surface relevant information, distill complex topics, generate custom content, and execute workflows—all while maintaining robust security and data governance controls.

How Travelers Insurance classified emails with Amazon Bedrock and prompt engineering

In this post, we discuss how FMs can reliably automate the classification of insurance service emails through prompt engineering. When formulating the problem as a classification task, an FM can perform well enough for production environments, while maintaining extensibility into other tasks and getting up and running quickly. All experiments were conducted using Anthropic’s Claude models on Amazon Bedrock.

How Cato Networks uses Amazon Bedrock to transform free text search into structured GraphQL queries

Accurately converting free text inputs into structured data is crucial for applications that involve data management and user interaction. In this post, we introduce a real business use case from Cato Networks that significantly improved user experience. By using Amazon Bedrock, we gained access to state-of-the-art generative language models with built-in support for JSON schemas and structured data.