Predictive AI that reaches production, and stays there.
Forecast demand, score risk, detect fraud, and explain every prediction to a regulator. Built on the AutoML engine that has run inside banks and telcos for a decade, and now driven by the H2O AI Super Agent.
- Predictive AI in H2O AI Cloud covers AutoML, explainability, deep learning, a tabular foundation model, a feature store, and MLOps.
- H2O Driverless AI has shipped AutoDoc (automatic model documentation) and AutoMLI (reason codes, K-LIME, Shapley) since 2017.
- TabH2O is a tabular foundation model that returns predictions without training, under three seconds on 15,000 rows.
- Commonwealth Bank of Australia scores 16 million customers in real time on H2O.ai and cut scam losses by 76%.
- The Data Science Agent in the H2O AI Super Agent drives these engines from a plain-English request.
Predictive AI turns historical data into forecasts, risk scores, and fraud signals a business can act on.
Building the model is the easy part. Predictive programs break in four predictable places, from the data that goes in to the drift that sets in.
- 01UntraceableFeatures get rebuilt for every project, training and serving drift apart, and nobody can say which data trained the model that's in production.
- 02UnreproducibleToo many approaches run for too long, and the winning model can't be repeated. The deep-learning work needs a research team you don't have.
- 03UnexplainableThe model works and no one can say why. Risk review drags for weeks, then sends it back for documentation that was never written.
- 04UndetectedScoring quietly misses its SLA and accuracy drifts with no alert. There is no rollback, so the only fix is to start a whole new project.
Every stage automated. Every stage explainable.
H2O.ai built a component for each of those failures, then connected them into one platform. A model goes from raw data to a governed endpoint in production without ever leaving it.
- Automated feature engineeringFeature engineering by evolutionary search, model selection, hyperparameter tuning, and ensembling, on GPU. Bring your own recipes as first-class citizens.
- Explainability built inAutoDoc writes the model documentation. AutoMLI gives K-LIME, Shapley, surrogate trees, disparate impact, and a reason code for every prediction, shipping since 2017.
- Predictions without trainingSend labeled and unlabeled rows, get predictions back. No training run, no tuning, no artifact to deploy, in under three seconds on 15,000 rows.
- No-code deep learningImage, text, video, and audio models from Kaggle Grandmaster defaults. Transfer learning, multi-GPU, and one-click packaging into MLOps, no research team needed.
- Features, defined onceOne catalog with 40+ attributes per feature. Offline for training, online for sub-millisecond serving, with drift alerts that can trigger retraining.
- Deploy, govern, monitorDeploy any model with one-click rollback. Drift, accuracy, and fairness monitors retrain on threshold, with an audit log for every scoring request.
The tools providing Predictive AI capabilities.
Ask for the model. The Super Agent builds it.
The Data Science Agent is one of nine agent types in the H2O AI Super Agent. It drives Driverless AI, runs H2O-3 in Notebook Engine, calls TabH2O for instant predictions, and hands the result to MLOps. It does not replace the engines. It operates them, with the same AutoDoc and reason codes attached to everything it produces.
One lane from data to decision. Observability underneath all of it.
The Feature Store feeds the training engines and, separately, feeds TabH2O for instant predictions. MLOps serves models to apps and APIs. The Super Agent drives the engines. Highlighted boxes are Predictive AI.
You operate it, or H2O.ai operates it for you.
Same platform either way: the same capabilities, the same governance, and the same audit trail. The choice stays open, so you can switch between them as the business changes, without rebuilding what runs on top.
H2O AI Cloud for Government
H2O AI Cloud for Government is FedRAMP High certified, delivering the highest standard of cloud security so federal agencies can harness predictive and generative AI without compromising data sovereignty or compliance.
In production where the numbers are audited.
:quality(75))
:quality(75))
Each turn made the lifecycle simpler for the people who run it.
AutoML automated the science. AutoAI automated the outcome. Agentic AI automates the thinking. Each era absorbed the one before it, and H2O.ai kept building through all three.
- 2017AutoML ships.AutoML in H2O-3 and Driverless AI ship with AutoDoc and AutoMLI. Explainability from day one.
- 2022No-code deep learning.Hydrogen Torch arrives; Feature Store co-developed with AT&T.
- 2024One platform.Notebook Labs and AI Engine Manager land in H2O AI Cloud.
- 2026TabH2O.A tabular foundation model, predictions with no training run at all.
- 2026The Data Science Agent.Drives the whole lane from a sentence. Gartner Visionary, fourth year running.
Other capabilities in H2O AI Cloud.
Questions people ask before they call us.
H2O Driverless AI is an award-winning AutoML tool that automates feature engineering, model selection, hyperparameter tuning, and ensembling, and generates AutoDoc model documentation and AutoMLI interpretability (K-LIME, Shapley, surrogate trees, disparate impact, reason codes) with every model. It has shipped since 2017.
See a model go from raw data to a governed endpoint in one session.
Bring a dataset. We will run the lane end to end with you, AutoDoc included, on H2O AI Managed Cloud or in your own environment.