AWS Fargate

AWS Fargate is a serverless, pay-as-you-go compute engine for containers that lets teams run Amazon ECS tasks and Amazon EKS pods without managing servers, with use cases including web apps, APIs and microservices, application modernization, AI and ML applications and data processing.

Official product page

4published use cases

3industries

3countries on record

Generative AI

top AI capability

Evidence mix: High 4 · Medium 0 · Low 0 — bands are computed from each record's evidence signals.

Industry

Country

4 use cases

CybersecurityAgentic AIGenerative AI

CyberArk combines Apache Iceberg and Amazon Bedrock AI agents to cut support case resolution time up to 95%

CyberArk redesigned its technical support pipeline using AWS Fargate, PyIceberg and Amazon Bedrock (Claude 3.7 Sonnet) to auto-generate grok patterns for parsing diverse vendor log formats into Iceberg tables, and built autonomous AI agents that query Athena and CyberArk's knowledge base to perform root-cause analysis from natural-language questions. The system cut case resolution time by up to 95% (complex cases from up to 15 days to 2-4 hours), let engineers handle up to 4x more cases per day (from 2-3 to 8-12), and made logs queryable within minutes instead of hours or days.

CyberArkAmazon Bedrock · Apache Iceberg · AWS Fargate +5

AutomotiveGenerative AIComputer VisionLarge Language Models

Ferrari Advances Generative AI for Customer Personalization and Production Efficiency

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.

Ferrari S.p.A.· ItalyAmazon Bedrock · Amazon Personalize · Amazon SageMaker JumpStart +5

Financial ServicesGenerative AIMachine LearningDocument Intelligence

CarbonTrail cuts generative AI costs by 88% for sustainable emissions intelligence using Amazon Bedrock

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.

CarbonTrail· New ZealandAmazon Bedrock · AWS Inferentia · AWS Fargate +3

Financial ServicesRetrieval-Augmented GenerationGenerative AILarge Language Models

NewDay lifts generative AI agent-assist accuracy from 60% to over 90%

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.

NewDay· United KingdomAmazon Bedrock · AWS Fargate · AWS Lambda +8