H2O Driverless AI
H2O Driverless AI automates machine-learning work such as feature engineering, model building, visualization and interpretation.
What H2O Driverless AI is
H2O Driverless AI automates machine-learning work such as feature engineering, model building, visualization and interpretation. Its workflow also covers model validation, tuning and selection, then can generate scoring pipelines. Explanations are available for both overall model behavior and individual predictions. Models can be deployed as REST endpoints, cloud services or optimized Java code for edge devices. The product supports NVIDIA GPUs, IBM Power 9 and Intel x86 CPUs, as well as GPU-accelerated algorithms including XGBoost, TensorFlow and LightGBM. Listed integrations include Kubernetes, Kubeflow, SageMaker, Alteryx, Jupyter/Python, KDB, Qlik, Trifacta and UiPath; data sources include HDFS, cloud storage services, Snowflake, JDBC, Databricks and Delta Table. Cloud installation options include H2O AI Cloud, AWS, Azure and Google Cloud. A 21-day evaluation license is available for public cloud use, plus a guided two-hour cloud test drive. Its default installation disables security, so production use calls for secure installation. Commercial licensing requires contacting sales; the entry lists a free pricing model but no free plan.
Good
- Automates feature engineering and model selection
- Explanations for global and individual predictions
- REST, cloud-service and Java deployment options
- Documented integrations and data connectors
- 21-day public-cloud evaluation license
Watch out
- Commercial license requires contacting sales
- Default installation has security disabled
- Windows and macOS laptops are for small exploratory datasets
Who it suits
Driverless AI is aimed at data scientists, DevOps and IT professionals, and business analysts. It may suit teams seeking automated model workflows and several deployment formats.
Verdict
Driverless AI automates multiple stages of model work and supports several deployment routes. Plan for secure production configuration and confirm commercial licensing with sales.
Plans and prices
From H2O Driverless AI's own pricing page, checked 4 Oct 2026.
| Plan | Price | What it gives you |
|---|---|---|
| H2O Driverless AI | Priced on request | Commercial license required; contact sales for purchase information |
The facts
Each one read from H2O Driverless AI's own pages, with the date it was checked.
What it does
- Authentication
- Supported authentication methods include client certificate, LDAP, local, mTLS, OpenID, and PAM; unvalidated authentication is the default.checked 4 Oct 2026
- Cloud availability
- Cloud installation options include H2O AI Cloud, AWS, Azure, and Google Cloud.checked 4 Oct 2026
- Data connectors
- Documented data sources include HDFS, Amazon S3, Azure Blob Storage, Google BigQuery, Google Cloud Storage, Snowflake, JDBC, Databricks, and Delta Table.checked 4 Oct 2026
- Deployment
- Models can be deployed as REST endpoints, cloud services, or optimized Java code for edge devices.checked 4 Oct 2026
- Explainability
- It provides explanations of model output at global and individual prediction levels.checked 4 Oct 2026
- Hardware and algorithms
- The product supports NVIDIA GPUs, IBM Power 9 and Intel x86 CPUs, and GPU accelerated algorithms including XGBoost, TensorFlow, and LightGBM.checked 4 Oct 2026
- Integrations
- Documented integrations include Kubernetes, Kubeflow, SageMaker, Alteryx, Jupyter/Python, KDB, Qlik, Trifacta, and UiPath.checked 4 Oct 2026
- Intended users
- H2O describes data scientists, DevOps and IT professionals, and business analysts as audiences for Driverless AI.checked 4 Oct 2026
- Model workflow
- It automates model validation, tuning, selection, interpretability, and scoring pipeline generation.checked 4 Oct 2026
- Security configuration
- The documentation warns that security is disabled in a default installation and recommends a secure installation for production.checked 4 Oct 2026
- What it does
- Driverless AI automates feature engineering, model building, visualization, and interpretability.checked 4 Oct 2026
The company
- Founded
- 2012checked 28 Sep 2026
- Headquarters
- Mountain View, California, United Stateschecked 28 Sep 2026
Where it runs
- Installation platforms
- The download documentation lists Linux packages, Windows 10 Pro Docker, and macOS Docker, and cautions that Windows and macOS laptops are intended only for small exploratory datasets.checked 4 Oct 2026
Money
- Trial
- H2O offers a 21-day evaluation license for public cloud use and a two-hour H2O Aquarium Cloud test drive with guided tutorials.checked 4 Oct 2026
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