AWS Generative AI Innovation Center powers 13 source-linked AI deployments documented in AIUseCaseHub, across 9 industries and 4 countries. Documented deployments include AI agents, RAG.
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Use Cases
13
Industries
9
Countries
4
Agent Cases
2
Hyperscaler mix
Filter AWS Generative AI Innovation Center's implementations by cloud provider evidence.
How AWS Generative AI Innovation Center builds AIBuild, Buy & Compose — what they mean
KONE, a global elevator and escalator company, built a generative AI assistant on AWS to help field technicians troubleshoot issues faster using confidential documentation, maintenance reports, and IoT data.Technicians access the assistant through a mobile app called Technician Assistant as a first step before escalating to technical help desks.The solution emphasizes security, privacy, least-privilege access, data minimization, and encryption with AWS Key Management Service.
Strava delivers personalized insights through Athlete Intelligence powered by Claude in Amazon Bedrock.The feature helps users understand complex workout data such as pace, power, distance, and segments in a friendly, encouraging brand voice.Strava worked with AWS generative AI experts to select Claude Haiku and used Amazon Bedrock Guardrails to improve content safety and quality.
Exact Sciences, through its PreventionGenetics subsidiary, uses AWS to accelerate variant curation and phenotype abstraction for genetic testing.The company manually reviewed scientific literature and patient clinical notes to interpret genetic variants that may cause rare disease or indicate elevated risk, and needed to speed turnaround for clinicians and patients.Working with the AWS Generative AI Innovation Center, Exact Sciences built the Variant Curation Accelerator and a phenotype abstraction tool on Amazon Bedrock, with human review, citations, source PDFs, and highlighted supporting text to improve trust and accuracy.
DoorDash, a local commerce platform, wanted to enhance self-service support for Dashers, Consumers, and Merchants by reducing live agent interactions and improving contact center user experience.Collaborating with AWS Generative AI Innovation Center, DoorDash built a voice-operated generative AI self-service contact center solution using Amazon Bedrock foundation models (Anthropic Claude) and Amazon Connect Customer, implementing retrieval-augmented generation from public help center data for accurate response.The AI-powered contact center handles hundreds of thousands of calls daily, reducing agent transfers by 49%, improving first contact resolution by 12%, and cutting development time by 50%.The solution operates with response latency of 2.5 seconds or less, is fully rolled out to all Dashers, and achieves $3M annual operational cost savings with plans for expansion.
Kipu Health, a behavioral health technology company serving more than 4 million patients across thousands of facilities, needed to automate compliance checks for clinical notes that were previously handled manually.Manual compliance scoring was time-consuming, error-prone, and difficult to keep up with changing provider-, state-, and discipline-specific requirements, creating risk of rejected notes and insurance revenue loss.
BMW Group, a global luxury vehicle manufacturer, faced the challenge of optimizing cloud infrastructure across 450+ DevOps teams and managing over 450 AWS accounts with business-critical applications.To increase operational efficiency and scale cloud governance, BMW Group developed the In-Console Cloud Assistant (ICCA), a generative AI conversational assistant powered by Amazon Bedrock. The ICCA understands natural language requests and helps DevOps teams monitor performance, identify bottlenecks, and optimize cloud resource usage.The solution leverages large language models accessed through Amazon Bedrock and is hosted securely within BMW's AWS Cloud Room environment, ensuring customer data is protected. The ICCA enables faster cloud governance scaling, cost reductions, accelerated time to market, and secure high-quality digital experiences for BMW's connected vehicle users worldwide.
Volkswagen Group worked with the AWS Generative AI Innovation Center to build an end-to-end marketing image generation and evaluation pipeline.The solution uses Amazon SageMaker AI endpoints for DreamBooth fine-tuning and Flux.1-Dev with LoRA inference, Amazon Nova Lite for prompt optimization, Amazon Bedrock with Claude 4.5 Sonnet for image and brand guideline evaluation, AWS Step Functions for orchestration, and Amazon S3 for storage.The team also hosted Florence-2 on SageMaker for component segmentation and used Amazon Nova Model Customization with synthetic data to fine-tune Nova Pro for brand-specific evaluation.
Toyota Motor Europe (TME) built a proof of concept with Deloitte and the AWS Generative AI Innovation Center to automatically generate documentation from legacy NCL source code.The solution produces technical YAML documentation, business HTML reports, and Mermaid process-flow diagrams from a legacy warranty-handling application, using Amazon Bedrock, Strands Agents SDK, Amazon Bedrock AgentCore, and an Amazon Bedrock Knowledge Base.The workflow uses agentic orchestration, retrieval-augmented generation, and bottom-up diagram composition to overcome context-window limits and preserve embedded business logic for modernization.
Associa, North America’s largest community management company, oversees approximately 7.5 million homeowners with 15,000 employees across more than 300 branch offices.The company manages approximately 48 million documents across 26 TB of data, but its existing document management system lacked efficient automated classification capabilities, creating manual bottlenecks and operational delays.Associa collaborated with the AWS Generative AI Innovation Center to build a generative AI-powered document classification system integrated into existing workflows using the GenAI IDP Accelerator on AWS.
The United States Environmental Protection Agency (EPA) worked with the AWS Generative AI Innovation Center to build proof-of-concepts that improve chemical study evaluation and data evaluation record creation.The solution uses Amazon Bedrock with Claude 3.7 Sonnet, Amazon Textract, Amazon Bedrock Guardrails, Amazon Bedrock Knowledge Bases, Amazon Titan embeddings, Amazon OpenSearch Service, Amazon S3, and Amazon DynamoDB.Scientists review AI-generated outputs, query source documents through a chatbot, and retain full human control over the final scientific determinations.
VideoAmp, a media measurement company, worked with the AWS Generative AI Innovation Center to develop a prototype natural-language analytics chatbot for its media analytics data.The solution is designed to let non-technical users ask questions in natural language and receive SQL-generated answers, summaries, and retrieved data from VideoAmp's analytics warehouse.
MSD collaborated with AWS Generative AI Innovation Center to build a text-to-SQL generative AI solution for complex healthcare databases.The system helps analysts and data scientists turn natural-language questions into executable SQL, reducing manual query writing and improving access to data for decision-making.