Amazon Bedrock
30 use cases using this technology
Attensi Uses the Power of AI to Reduce the Time It Takes to Develop Content by up to 95%
Attensi
Norwegian gamified-training software company Attensi enhanced its Creator authoring tool and simulation training platform with generative AI built on AWS services including Amazon Bedrock, Amazon SageMaker, and Amazon EKS, plus AWS Partner Hugging Face. The AI features generate dialogue, tasks and minigames, translate text, and convert text to speech, cutting content-creation time by 90-95% with Creator's AI copilots. Attensi's aggregate customer data shows game-based training drives a 19% productivity increase, 5x faster time to competence, 85% knowledge-gap closure, 2.5x revenue growth, and 75% attrition reduction.
Zalando enhancies customer engagement and operational efficiency with Mistral
Zalando
Zalando, a European e-commerce platform, integrated Mistral models hosted on AWS Bedrock into its platform to add natural language processing and machine learning capabilities. The integration supports personalized recommendations, improved customer service and streamlined operations for the retailer's shopping experience.
Miroglio Group Unleashes Fashion Innovation in Italy with Generative AI on AWS
Miroglio Group
Italian fashion company Miroglio Group, which designs and distributes 10 fashion and lifestyle brands across 41 countries, worked with AWS Partner Data Reply to replace its manual product-tagging process with a generative AI-powered tagging system built on Amazon Bedrock using Anthropic's Claude 3.5 Sonnet, combined with a machine learning model trained on the company's historical images. The system analyzes product images and generates accurate technical and editorial tags and descriptions across multiple languages, reaching almost 90 percent accuracy and cutting a task that previously took one month down to about one hour.
N26 automates customer operations with Claude
N26
N26, a fully licensed digital bank serving customers across 24 European markets, deployed Claude via AWS Bedrock in Europe to automate document-heavy customer service workflows. Since 2024, N26 has integrated Claude into more than 15 internal applications: a customer-facing virtual assistant providing instant support in five languages, automated chargeback handling that translates documentation and recommends decisions on complex cases, processing of incoming physical claim letters, and financial crime analysis where Claude synthesizes customer data and auto-drafts investigation reports. One year after implementation, N26 automated up to 70% of tasks across targeted processes and reduced manual processing by up to 50% in specific processes.
Novo Nordisk accelerates clinical documentation and drug development with Claude
Novo Nordisk
Novo Nordisk, a global pharmaceutical company headquartered in Europe, built NovoScribe, an AI-powered documentation platform using Claude Code, Amazon Bedrock and MongoDB Atlas, to automate clinical study report (CSR) generation. Claude helped cut writing times on CSRs by 90%, reducing time spent producing clinical study documentation from 10+ weeks to 10 minutes, and delivered a 95% reduction in resources needed to create device verification protocols. The platform expanded from clinical trial reports to device protocol documentation and patient materials, and an 11-person development team, including non-technical staff, now prototypes features using Claude Code.
Bynder Reduces Search Time by 75% Using Amazon Bedrock with Amazon Titan Multimodal Embeddings
Bynder
Bynder, a digital asset management company serving over 4,000 companies globally and storing more than 175 million assets (18 PB of data), built visual-similarity search using Amazon Titan Multimodal Embeddings in Amazon Bedrock. The solution converts images and search queries into vectors to match by visual and contextual similarity. One Bynder customer reports that time spent searching for assets for a typical campaign task decreased by 75%, and search results return approximately 50% more relevant options on average. Bynder does not use customer data to train the underlying large language model. The company is now exploring frame-by-frame video indexing.
Swindon Borough Council makes public information accessible with an Easy Read generative AI tool built on Amazon Bedrock
Swindon Borough Council
Swindon Borough Council, a local authority in England, built an Easy Read solution using Amazon Bedrock to make council documents accessible to residents with learning disabilities, low literacy or cognitive impairment. The generative AI summarizes and simplifies complex text and generates matching images, presenting simplified text alongside images on the page. The council tested the tool on a complex tenancy agreement over 50 pages long and, working with a group of Experts by Experience of a Learning Disability, refined the format based on their feedback. Combined with the council's existing Translate solution, content can be produced in 75 languages. Manually adapting a five-page document into Easy Read format previously cost around £500 and took two weeks; the council can now create an accessible multi-page document for 7-10 pence per page. The council plans to make the tool open source for other councils to use.
AWS Partner Adastra Supports KWS in Generative AI Adoption Using Amazon Bedrock
KWS
KWS, a global seed producer, uses Amazon Bedrock and generative AI to boost research speed and efficiency, supported by Adastra, an AWS Partner. Access to Amazon Bedrock's large language models gives KWS flexibility to prototype and test generative AI use cases without the cost of setting up its own large IT infrastructure, according to Bjørn Øst Hansen, KWS's senior research lead for knowledge discovery.
Epilot reduces email processing time by 87% using Amazon Bedrock
Epilot
Cologne, Germany-based Epilot, which provides an extended-relationship-management (XRM) platform for energy companies, built an AI email-summarization feature on Amazon Bedrock (Anthropic's Claude via serverless AWS Lambda/SQS architecture) that summarizes long customer email threads for its 170+ energy-sector customers. Epilot generates 55,000 AI email summaries monthly with a negligible failure rate; about 80% of users say the feature simplifies their work, and users save 87% of the time previously spent on email management. Epilot also built a 'suggested actions' feature that auto-updates customer records from email content with a human in the loop, and keeps all processed data within an EU AWS Region using Amazon Bedrock's zero-retention data policy.
Aareon builds AAVA, an AI virtual assistant integrated into its German property-management ERP, using Amazon Bedrock
Aareon
Aareon, a Germany-headquartered property management software provider, integrated an AI virtual assistant called AAVA into its German ERP solution Wodis Yuneo using Amazon Bedrock. AAVA lets real estate housing company customers query documents, request information through chat, automate processes, and accelerate workflows -- including scheduling appointments between tenants and craftsmen, coding invoices, analyzing images to draft damage reports, and sorting incoming email, with both text and voice support. Aareon uses various LLMs available through Bedrock, including Anthropic's Claude models and Amazon Nova models, testing and selecting models by complexity and price performance for each use case (for example, a higher token-limit model for calculating service charges). The Bedrock deployment runs in the AWS Germany (Frankfurt) Region to help meet GDPR requirements, with customer data not used to train or improve the underlying models. The first version of AAVA was built in 4 weeks and announced to customers within 6 months, developed with support from AWS Partner Reply.
Ferrari Advances Generative AI for Customer Personalization and Production Efficiency
Ferrari S.p.A.
Ferrari built a car configurator on AWS using LLMs in Amazon Bedrock and Amazon Personalize, letting customers personalize their vehicle across millions of possible configurations with 3D visualization, which increased sales leads and cut configuration times by 20%. Ferrari also fine-tuned Amazon Titan, Claude 3 and Llama models in Bedrock (combined with Amazon SageMaker JumpStart) on its own documentation to power an after-sales generative AI chatbot that classifies and summarizes customer care tickets, and uses Amazon Lookout for Vision to automate quality inspection and defect detection on the assembly line. Generative AI is also used to run vehicle design simulations and text-to-image prototyping to reduce reliance on physical prototypes.
Pfizer saves 16,000 hours annually with generative AI search through the PACT initiative
Pfizer
Pfizer and AWS created the Pfizer-Amazon Collaboration Team (PACT) initiative in 2021, pursuing 14 rapid-prototyping projects applying AWS analytics, ML and generative AI to laboratory, clinical manufacturing and supply chain challenges. Using Amazon Kendra and, later, Anthropic's Claude 2.1 via Amazon Bedrock (accessed through an internal voice/chatbot platform called Vox), Pfizer estimates scientists save up to 16,000 hours of document search time annually and cut related infrastructure costs by 55%. A separate PACT prototype uses Amazon SageMaker, Amazon Lookout for Equipment and Amazon Lookout for Metrics to detect anomalies in Pfizer's continuous manufacturing (PCMM) process. Five of the initial 14 PACT projects have moved into production.
CarbonTrail cuts generative AI costs by 88% for sustainable emissions intelligence using Amazon Bedrock
CarbonTrail
New Zealand-based CarbonTrail built an AI-powered emissions measurement platform and CarbonAPI on AWS, running a document-analysis pipeline on Amazon Bedrock and workloads on AWS Inferentia to process bank-scale invoice and transactional data. The platform achieves an 87% reduction in processing time and 88% lower cost than a comparable GPT-4-with-embeddings approach, and reduces low-confidence classifications by up to 40%. The Bank of New Zealand (BNZ) uses CarbonTrail's CarbonAPI to progress toward measuring emissions across its SME customers.
Building a central data, analytics, and AI solution using AWS with Generali
Generali
Insurance and asset management group Generali built a central data, analytics and AI solution on AWS to standardize AI adoption across its more than 40 operating entities, using Amazon Redshift for the central data warehouse, AWS Glue for data-quality and transformation pipelines, Amazon SageMaker AI to automate claim settlement and predictive payout modeling, and Amazon Bedrock to power a generative AI customer-assistance agent providing instant responses. The company developed 16 flagship AI use cases spanning pricing, underwriting, claims processing and operations, deployable across operating entities via a centralized Global AI engine, while complying with GDPR and internal governance policies.
Multitudes Builds Code Review Quality Feature in 2 Months Using 3 LLMs on Amazon Bedrock
Multitudes
Multitudes, a New Zealand-based engineering analytics startup, used Amazon Bedrock to build a code review quality feature, testing over 10 large language models across roughly 1,000 code reviews before choosing Amazon Nova Pro for bot detection, Anthropic Claude for feedback specificity and prompt-injection detection, and Mistral for sentiment analysis, orchestrated with Amazon Elastic Container Service. The feature increased monthly active users by 44 percent within two months of launch and reduced severe misclassification rates from 20 percent to under 1 percent.
BMW Group Delivers Generative AI-Based Cloud Optimization Assistant (ICCA) Using AWS
BMW Group
BMW Group developed the In-Console Cloud Assistant (ICCA), a conversational generative AI assistant built with Amazon Bedrock, to help its 450+ DevOps teams across more than 450 AWS accounts monitor performance, identify bottlenecks, and detect optimization opportunities. Built with the AWS Generative AI Innovation Center, ICCA keeps data within the BMW Cloud Room hosted on AWS and has helped BMW scale cloud governance and reduce costs and time to market.
Banking Innovator bunq Supports Growth, Strengthens Security Using AWS
bunq
bunq, a Dutch neobank with over 11 million users across Europe, uses Amazon Bedrock for several generative AI use cases including summarizing new user data with large language models, removing the need for agents to process onboarding documents manually. Using Amazon Bedrock, bunq tripled user support process efficiency while maintaining over 90 percent accuracy. Sensitive data stays within bunq's AWS virtual private cloud, supporting GDPR and PCI DSS compliance alongside tools such as AWS CloudHSM, AWS Security Hub and AWS KMS.
Foxintelligence Enhances Ecommerce Insight Using AWS and Generative AI
Foxintelligence
Foxintelligence by NielsenIQ, the largest ecommerce measurement and consumer analytics company in Europe with around 5 million active online buyers tracked, uses Amazon SageMaker to build, train, and deploy its machine learning models and is exploring Amazon Bedrock to access foundation models, fine-tune them, and do prompt engineering, reducing time to market for generative AI innovation. As a company handling consumer personal data, Foxintelligence relies on AWS security features to comply with the EU's General Data Protection Regulation (GDPR) and other regional regulations as it expands globally, with advice from the AWS engineering team on new compliance features.
Atlante focuses on sustainability and growth using generative AI and AWS
Atlante
Atlante, the fast and ultra-fast EV charging network for Southern Europe, built its platform from scratch on AWS using serverless and fully managed services. Atlante's data science team uses generative AI services including Amazon Q and Amazon Bedrock, and is able to track carbon emissions, helping the startup increase efficiency and save money while protecting the planet.
Siemens increases global search speed 3x and cuts costs 70% using Amazon Nova
Siemens AG
Siemens wanted to help its customers navigate its many business and product lines to find what they need without sifting through multiple websites. Using AWS, the company implemented generative AI to optimize its global search: users can now enter queries in natural language and receive the most relevant information in seconds. Siemens eliminated no-results searches and improved global search speed. With access to Amazon Nova models in Amazon Bedrock, responses are three times faster, giving clients across industries high-quality information while reducing costs by 70 percent.
Contra Costa County District Attorney's Office Makes Unbiased Charging Decisions with ScaleCapacity Generative AI Solution on AWS
Contra Costa County District Attorney's Office
The Contra Costa County District Attorney's Office worked with AWS Partner ScaleCapacity to build a Race-Blind Charging solution to comply with California's AB 2778 mandate. The solution uses Amazon Bedrock and Amazon Textract to automatically redact race, ethnicity and other identifying details from police reports and case documents before charging decisions are made, with Amazon S3, DynamoDB, Cognito and SES supporting document storage, metadata and user access. The office processes around 17,000 cases annually, achieved compliance in six months, and can test and deploy new redaction rule changes in under a week.
Reveleer processes 45 million pages of medical records quarterly with AI on AWS
Reveleer
Healthcare data and analytics company Reveleer uses Amazon Textract and Amazon Comprehend Medical to scan medical chart data and identify diagnostic conditions with high accuracy for value-based care programs, highlighting findings for medical coders so they don't have to manually review thousands of pages per patient. The Reveleer platform maintains 100% uptime with 90% of responses served in under 8 seconds, and processed over 45 million pages of medical chart data in the first quarter of 2024. Reveleer plans to add Amazon Bedrock foundation models to its platform.
Ferrari increases custom vehicle configurations 20% with Amazon Bedrock generative AI
Ferrari
Ferrari used Amazon Bedrock to access and benchmark multiple foundation models, delivering a 20% increase in custom vehicle configurations and boosting productivity for over 1,000 technical users via a generative AI-powered knowledge base. Ferrari also built an AWS-enabled Car Configurator for immersive virtual vehicle configuration and achieved up to 60% faster simulations for customized models.
Myriad Genetics speeds document processing with AWS GenAI Intelligent Document Processing Accelerator
Myriad Genetics
Myriad Genetics partnered with the AWS Generative AI Innovation Center to replace an Amazon Textract/Comprehend pipeline with Amazon Bedrock foundation models (Nova Pro for classification, Nova Premier for extraction) using the open-source GenAI IDP Accelerator. Document classification accuracy rose from 94% to 98%, classification cost per page fell 77% (3.1 cents to 0.7 cents), and classification time fell 80% (8.5 minutes to 1.5 minutes per document). Automated key information extraction reached 90% accuracy matching the manual baseline, with a projected $132K in annual savings and 300 hours saved monthly across 9,000 prior authorizations in the Women's Health unit alone.
Novo Nordisk Scales to 2,500+ Use Cases with Secure Generative AI Using Amazon Bedrock
Novo Nordisk
Novo Nordisk built a self-service generative AI platform on AWS, using Amazon Bedrock's foundation models, so employees could build and customize chatbots for nonregulated business use cases without needing to develop applications or maintain infrastructure themselves. The company worked with AWS Partner Cloud2 Oy (previously KeyCore) to validate the architecture for security and scalability. More than 25,000 Novo Nordisk employees have used the platform to create chatbots for over 2,500 unique use cases, such as retrieving information, drafting documents, or acting as a virtual colleague or critic. The company's general-purpose chatbot is used by more than 1,000 employees and processes over 26,000 prompts a month; its largest use case was trained on 140,000 documents. Each use case costs around $10 per month to run on AWS, using serverless services including Amazon DynamoDB and AWS Lambda. Building a chatbot now takes days rather than months, and some tasks that took a full day can be completed in as little as 10 minutes.
Using Amazon Bedrock Agents to Accelerate Decisions Across Drug Development at AstraZeneca
AstraZeneca
AstraZeneca built Development Assistant, a multi-agent AI tool using Amazon Bedrock Agents, that lets clinical, regulatory, safety and quality teams ask natural language questions and get insights from structured and unstructured data in seconds via text-to-SQL generation and retrieval-augmented generation. A supervisor agent routes queries to specialized subagents (terminology, clinical, regulatory, database). Built on AstraZeneca's Drug Development Data Platform (3DP), the tool moved from concept to production in 6 months, including cybersecurity and AI governance checks, and is scaling to over 1,000 users.
NewDay lifts generative AI agent-assist accuracy from 60% to over 90%
NewDay
NewDay, whose contact centre handles 2.5 million calls a year, built NewAssist, a generative AI assistant on Amazon Bedrock using Retrieval Augmented Generation, out of an internal hackathon. Through iterative experiments — including a custom parser for its knowledge base and injecting internal acronyms into prompts — NewDay raised NewAssist's accuracy from below 60% to over 90%, cut the average time to retrieve an answer from 90 seconds to 4 seconds, and rolled it out to over 150 agents, running on serverless AWS infrastructure for under $400 a month.
Forcura Expedites Patient Care Using Generative AI on Amazon Bedrock
Forcura
Forcura, a HITRUST-certified healthcare workflow management company serving over 900 healthcare providers representing about 1 million patients, added a generative-AI referral summary feature to its Referral Management product. Built on Amazon Bedrock using Anthropic's Claude 3 model family, the feature pulls key information such as patient demographics, clinical history and requested services into a concise summary. Forcura piloted the feature with three clients in April 2024 and reached general release within 90 days of the pilot start.
Workday Accelerates Generative AI / ML Product Development Using Amazon SageMaker
Workday
Workday uses Amazon SageMaker to let engineering teams build, train and deploy ML models, including LLMs, across AWS Regions to meet global customers' data-residency requirements. Using Amazon SageMaker Studio, Jumpstart and Ground Truth Plus, Workday piloted a closed-book ML application analyzing job descriptions, invoices and contracts, improving ML inference latency by a factor of five. Workday also received early access to Amazon Bedrock for generative AI prototyping. Head of Workday AI Shane Luke said the company has scaled from a thousand inference requests to tens of millions coming in daily.
Novartis: Accelerating Drug Development with AI-Powered Clinical Trial Transformation
Novartis
Novartis partnered with AWS Professional Services and Accenture to modernize their drug development infrastructure and integrate AI across clinical trials, with the goal of reducing trial development cycles by at least six months. The initiative built a GXP-compliant data mesh platform on AWS with Databricks for processing, enabling AI use cases including protocol generation and an intelligent decision system (digital twin). Early results from the patient safety domain showed 72% query speed improvements, 60% storage cost reduction, and 160+ hours of manual work eliminated. The protocol generation use case achieved 83-87% acceleration in producing compliant protocols.