Case Study: Intel achieves faster, trusted AI development with H2O.ai

Accelerate AI Development with H2O.ai on Intel Architecture

Intel needed to accelerate enterprise AI development while overcoming shortages of data-science talent, long iterative workflows, and concerns about model explainability and trust. To address these challenges Intel worked with H2O.ai, deploying H2O.ai’s software portfolio—including H2O Driverless AI, the H2O open source platform, and H2O Sparkling Water—validated on Intel®-based infrastructure.

H2O.ai’s integrated solution paired automated, explainable modeling and AutoML with Intel® Xeon® Scalable processors, Intel SSDs, and optimized libraries to speed development, improve scalability, and reduce cost. The validated stack trained 16 XGBoost models on a single Intel Xeon Platinum node in about 214 seconds, showed a 38.5% speedup when scaling from 3 to 5 Intel Xeon Gold nodes, and delivered reported TCO improvements (up to ~60% in certain replacement scenarios), demonstrating faster time-to-market, better model trust, and measurable performance gains from H2O.ai on Intel architecture.

Intel