Case Study: GEP achieves real-time AI-powered supply chain scalability with Confluent

GEP Boosts AI-Powered Supply Chain, Processing 1B Events per Month

GEP, an AI-first supply chain and procurement company, was struggling with slow quarterly batch processing and legacy data pipelines that delayed reporting and decision-making for customers. To support real-time operations, GEP turned to Confluent’s fully managed, cloud-native streaming platform to replace its self-managed Apache Kafka environment and connect operational, analytical, and AI systems.

With Confluent, GEP simplified data delivery using pre-built connectors, reduced pipeline sprawl, and scaled from 500K to 1 billion events per month across multiple clusters with zero data loss. Confluent helped GEP connect 500 microservices, improve outage prediction from 2 minutes to 30 minutes ahead, and boost predictive performance by 1,400%, while also lowering maintenance effort and enabling faster AI-powered customer experiences.

GEP

Nithin Prasad

Senior Engineering Manager