Back to Directory

AWS Lambda

22 use cases using this technology · by Amazon Web Services

22published use cases
13industries
9countries on record
Generative AI
top AI capability

Evidence mix: High 22 · Medium 0 · Low 0 — bands are computed from each record's evidence signals.

Industry
Country

22 use cases

Consumer GoodsAgentic AIGenerative AI

Vxceed builds a near real-time multi-agent AI platform using Amazon Bedrock

Vxceed, a global SaaS provider of AI-powered sales and distribution solutions for consumer packaged goods (CPG) companies, built a multi-agent AI platform on Amazon Bedrock to interpret store-level signals in near real time across traditional trade retail outlets. Specialized agents interpret field signals, summarize patterns, generate narrative explanations, and recommend next steps, and also collaboratively produce short AI-generated video news bulletins (script, audio, and visuals each by a different agent) summarizing daily risks and opportunities. Built with Amazon DynamoDB, AWS AppSync WebSockets, AWS Lambda, and AWS Step Functions, the platform processes about US$250 million in daily transactions for major customers, expanded outlet coverage from 1.6 million to over 2 million stores in 18 months, and delivered 5-10% sales uplift and 15-25% improvement in promotion ROI through earlier issue detection.

VxceedAmazon Bedrock · Amazon DynamoDB · AWS AppSync +2
EnergyNatural Language ProcessingGenerative AI

Epilot reduces email processing time by 87% using Amazon Bedrock

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.

Epilot· GermanyAmazon Bedrock · Anthropic Claude · AWS Lambda +1
ManufacturingComputer VisionFraud & Anomaly Detection

Siemens Electronics Factory Erlangen Reduces Machine Learning Deployment Time by 80% with AWS and Siemens Industrial AI on Industrial Edge

Siemens Electronics Factory Erlangen, which manufactures PCBs and controllers such as SINAMICS converters and SINUMERIK CNC controllers, used computer vision models to spot anomalies in PCB assembly, but training and retraining ML models on premises was time-intensive and constrained by GPU bottlenecks. The factory adopted AWS services together with Siemens Industrial Edge and Siemens Industrial AI, sending shopfloor images via Edge applications to Amazon S3 before training via Amazon SageMaker or AWS Lambda; training results and edge prediction results are monitored through AI Model Monitor, with AI Model Manager providing central management of models on the shopfloor. This reduced time spent on model training and retraining by 80 percent (from about 30 minutes to roughly 5 minutes for retraining and deployment), cut costs by more than 90 percent compared to on-premises data storage systems, and reduced the false call rate by over 50 percent, while continuously preventing around 4 percent of PCB assembly errors compared to around 60 percent at peaks in the past.

Siemens Electronics Factory ErlangenAmazon S3 · Amazon SageMaker · AWS Lambda +5
PharmaceuticalsGenerative AILarge Language ModelsAgentic AIConversational AI

Novo Nordisk Scales to 2,500+ Use Cases with Secure Generative AI Using Amazon Bedrock

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.

Novo Nordisk· DenmarkAmazon Bedrock · AWS Lambda · Amazon DynamoDB
InsuranceMachine Learning

How Mapfre Insurance modernized fraud claims with Amazon EMR Serverless

Mapfre Insurance, the number one auto and home insurer in Massachusetts, modernized fraud detection by combining graph-based features from Neo4j with machine learning models deployed on AWS, using Amazon EMR Serverless, Apache Iceberg tables on Amazon S3, AWS Glue Data Catalog, AWS Lake Formation, and Amazon MWAA for orchestration. Fraud predictions integrate directly with Guidewire Claims via AWS Lambda, automatically creating claim activities showing the top model drivers for adjusters. The initiative, covering Massachusetts Auto insurance and later expanded to Home insurance, has delivered more than $5 million in Net Present Value, with detection accuracy improved 50-135 percent compared to baseline methods.

Mapfre Insurance· United StatesAmazon EMR Serverless · Apache Iceberg · AWS Glue Data Catalog +5