Artificial Intelligence
Category: Customer Solutions
How E.ON plans to significantly reduce Metering costs annually with AI diagnostics for smart meters powered by Amazon Textract
E.ON’s story highlights how a creative application of Amazon Textract, combined with custom image analysis and pulse counting, can solve a real-world challenge at scale. By diagnosing smart meter errors through brief smartphone videos, E.ON aims to lower costs, improve customer satisfaction, and enhance overall energy service reliability. In this post, we dive into how this solution works and the impact it’s making.
How Kepler democratized AI access and enhanced client services with Amazon Q Business
At Kepler, a global full-service digital marketing agency serving Fortune 500 brands, we understand the delicate balance between creative marketing strategies and data-driven precision. In this post, we share how implementing Amazon Q Business transformed our operations by democratizing AI access across our organization while maintaining stringent security standards, resulting in an average savings of 2.7 hours per week per employee in manual work and improved client service delivery.
Build a Text-to-SQL solution for data consistency in generative AI using Amazon Nova
This post evaluates the key options for querying data using generative AI, discusses their strengths and limitations, and demonstrates why Text-to-SQL is the best choice for deterministic, schema-specific tasks. We show how to effectively use Text-to-SQL using Amazon Nova, a foundation model (FM) available in Amazon Bedrock, to derive precise and reliable answers from your data.
Modernize and migrate on-premises fraud detection machine learning workflows to Amazon SageMaker
Radial is the largest 3PL fulfillment provider, also offering integrated payment, fraud detection, and omnichannel solutions to mid-market and enterprise brands. In this post, we share how Radial optimized the cost and performance of their fraud detection machine learning (ML) applications by modernizing their ML workflow using Amazon SageMaker.
Impel enhances automotive dealership customer experience with fine-tuned LLMs on Amazon SageMaker
In this post, we share how Impel enhances the automotive dealership customer experience with fine-tuned LLMs on SageMaker.
Build a scalable AI assistant to help refugees using AWS
The Danish humanitarian organization Bevar Ukraine has developed a comprehensive virtual generative AI-powered assistant called Victor, aimed at addressing the pressing needs of Ukrainian refugees integrating into Danish society. This post details our technical implementation using AWS services to create a scalable, multilingual AI assistant system that provides automated assistance while maintaining data security and GDPR compliance.
Enhanced diagnostics flow with LLM and Amazon Bedrock agent integration
In this post, we explore how Noodoe uses AI and Amazon Bedrock to optimize EV charging operations. By integrating LLMs, Noodoe enhances station diagnostics, enables dynamic pricing, and delivers multilingual support. These innovations reduce downtime, maximize efficiency, and improve sustainability. Read on to discover how AI is transforming EV charging management.
How ZURU improved the accuracy of floor plan generation by 109% using Amazon Bedrock and Amazon SageMaker
ZURU collaborated with AWS Generative AI Innovation Center and AWS Professional Services to implement a more accurate text-to-floor plan generator using generative AI. In this post, we show you why a solution using a large language model (LLM) was chosen. We explore how model selection, prompt engineering, and fine-tuning can be used to improve results.
Real-world applications of Amazon Nova Canvas for interior design and product photography
In this post, we explore how Amazon Nova Canvas can solve real-world business challenges through advanced image generation techniques. We focus on two specific use cases that demonstrate the power and flexibility of this technology: interior design and product photography.
A generative AI prototype with Amazon Bedrock transforms life sciences and the genome analysis process
This post explores deploying a text-to-SQL pipeline using generative AI models and Amazon 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.









