The client was managing large datasets across disparate systems with no centralized intelligence layer. They faced
Manual data processing bottlenecks
Inconsistent model performance
Limited ML deployment capabilities
High infrastructure and maintenance costs
They needed a unified AI platform that could handle end-to-end ML operations—from data ingestion to model training, deployment, and monitoring.