Amazon SageMaker AI
3 use cases using this technology
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.
Figma trains AI Search models in 5 months using Amazon SageMaker AI
Figma
Design platform Figma built its AI infrastructure on Amazon SageMaker AI, using Amazon EMR with Apache Spark to process billions of design elements and the custom FigmaStep framework on SageMaker Pipelines to orchestrate training. Figma trained and deployed the models behind its AI Search feature within five months, launching it at Config 2024, and ran more than 10,000 SageMaker AI training jobs in 2025 to support features including the AI prompt-to-app tool Figma Make.
Phagos uses generative AI on AWS to match bacteriophages to bacterial infections
Phagos
Phagos, a Paris-based biotech startup, uses generative AI models built with Amazon SageMaker AI to match bacteriophages to target bacteria for phage therapy, replacing a manual trial-and-error process. The AI models cut wet-lab testing needs by 50% and reduced phage-candidate screening time by 99.5%, from 29 hours to 10 minutes per bacteria. Phagos has treated more than half a million animals in France and can now develop a new treatment in two months versus 10+ years for traditional antibiotic development.