Industrial Distributor
From churn-prediction pilot to fully automated AI in production on Azure
Situation
A global B2B industrial distributor had validated a customer churn AI model in a successful pilot, but the solution was maintained externally and run semi-manually. Retraining and inference required hands-on intervention each month, data extraction depended on a single internal owner, and recurring source-data quality issues forced constant firefighting - making it difficult to scale the insights across the commercial organisation.
Solution
We led the transition from an externally maintained pilot to a fully automated, production-ready system inside the company's own Azure environment. The churn model was re-architected around Azure Blob Storage, Azure SQL, and Azure ML Service, with orchestrated extraction, model training, inference, and Power BI refreshes. Logging, monitoring, error handling, a model registry, and end-to-end documentation were added so the internal team can operate, retrain, and evolve the solution without external dependencies.
Results
Churn prediction moved from a manual monthly ritual to a self-service capability the business can run on its own schedule. The solution is now fully owned inside the customer's Azure estate, with a clear audit trail, flexible retraining cadence, and a scalable foundation for future AI use cases across CRM, claims, and customer analytics.
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