Video by H2O.ai via YouTube
H2O.ai Managed Cloud is a fully managed, isolated AI environment where data preparation, model development, and deployment all run in one place.
This first lesson covers what the platform is and the problem it solves. Most teams are not short of ideas, they are slowed down by data living in one system, models being built in another, and deployment happening somewhere else.
You will also see the two principles behind the setup. Managed means H2O.ai runs the infrastructure for you, including GPU compute when the workload needs it. Isolated means your environment is dedicated, so data, compute, and workloads are never shared with another customer.
Covered in this video:
The three capabilities the platform brings together: automated machine learning, generative AI, and model operations
Why fragmented tooling causes delays, duplicated effort, and gaps in governance
Where H2O Driverless AI, H2O LLM Studio, and Enterprise h2oGPTe sit in the platform
What managed and isolated mean for security, privacy, and enterprise governance
LINKS
H2O.ai University: https://h2o.ai/university
Documentation: https://docs.h2o.ai
Request access or a demo: https://h2o.ai/demo
Support: support@h2o.ai
ABOUT H2O.ai
H2O.ai builds the platform enterprises use to develop, deploy, and operate AI on their own private data, across predictive machine learning and generative AI.
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