What You Can Build on H2O Managed Cloud
- H2O AI Managed Cloud
- H2O MLOps
This lesson maps what you can build on H2O Managed Cloud, structured around three pillars: modeling and automation, AI applications and data engineering, and deployment, monitoring, and governance. It covers predictive AI use cases like fraud detection, demand forecasting, credit risk, and churn, answering what is likely to happen. It covers generative AI use cases like enterprise assistants, document intelligence, summarization, and RAG, answering how to generate and automate knowledge. It closes by noting both approaches span structured and unstructured data, with secure deployment and monitoring built in.
Key takeaways
- What the three pillars of H2O Managed Cloud are: modeling, AI applications, and deployment with governance
- How predictive AI use cases like fraud detection and churn prediction answer what is likely to happen
- Why generative AI use cases like document intelligence and RAG focus on generating and automating knowledge
- The platform supports both structured data like transactions and unstructured data like text and images
- How deployment, monitoring, and governance are built directly into the platform for production reliability
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