Technology & SoftwareComputer Vision

IDENTT builds a scalable, secure, AI-powered identity verification solution on AWS

IDENTTAmazon Elastic Kubernetes Service · Amazon EC2 Auto Scaling · Amazon SageMaker

IDENTT, which provides biometric and document-verification identity checks to banks, fintechs, public sector organizations and gambling operators across 16 countries, moved off on-premises GPUs to AWS to design, train and host its fraud-detection AI models at scale using Amazon EKS and Amazon SageMaker. The move achieved up to 60% GPU cost savings versus on-premises infrastructure, cut ML iteration cycles from weeks to hours, and let IDENTT deploy to new AWS regions in minutes to onboard customers in new countries.

Overview

IDENTT, which provides biometric and document-verification identity checks to banks, fintechs, public sector organizations and gambling operators across 16 countries, moved off on-premises GPUs to AWS to design, train and host its fraud-detection AI models at scale using Amazon EKS and Amazon SageMaker. The move achieved up to 60% GPU cost savings versus on-premises infrastructure, cut ML iteration cycles from weeks to hours, and let IDENTT deploy to new AWS regions in minutes to onboard customers in new countries.

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The challenge

With the rise of deepfakes and other sophisticated forms of fraud, IDENTT needed a cost-effective, globally scalable infrastructure to research, develop and deliver biometric and document verification AI models, after outgrowing its on-premises GPUs.

The solution

IDENTT moved to AWS, running containerized microservices on Amazon EKS with automatic scaling and on-demand GPU capacity via Amazon EC2 Auto Scaling, plus Amazon SageMaker, to design, train and host its identity-verification AI models, deploying to new AWS Regions in minutes to meet regional data-residency and compliance requirements.

Computer VisionFraud & Anomaly Detection

Reported business value

IDENTT achieves up to 60 percent GPU cost savings compared to on-demand GPUs versus on-site infrastructure, cut ML iteration cycles for detecting new fraud techniques from weeks to hours, and can deploy to new AWS Regions in minutes, reducing onboarding time for new customers.

Sources

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