Case Study: Leading Handset Manufacturer achieves 20% improvement in recommendation relevance and 1500x faster runtime with EdgeVerve

Leading Handset Manufacturer - Customer Case Study

Leading Handset Manufacturer was building a mobile video streaming service to monetize content delivery and drive additional movie sales and rentals. Their legacy recommendation engine ran on an older Hadoop/Mahout stack and, despite a large in‑house modeling team, suffered from slow runtimes and suboptimal accuracy. EdgeVerve was engaged to improve speed and relevance.

EdgeVerve implemented a machine‑learning recommender system that, in less than a week, delivered a 1500x execution speedup and improved recommendation relevance by 20%. The EdgeVerve solution is interpretable, better captures user preferences, and supports diverse recommendations without excessive obscurity, improving the platform’s monetization potential.