H2O.ai
H2O.ai unifies generative and predictive AI for regulated enterprises, delivering private, air‑gapped agents, AutoML, and model operations. It integrates with existing apps, supports on‑prem and VPC deployments, and emphasizes accuracy, cost controls, and governance across the full ML lifecycle.
Overview
Teams ingest private documents and data into h2oGPTe and vertical agents, connect repositories like SharePoint, Slack, and Google Drive, and add predictive models from H2O Driverless AI or H2O‑3. Agents research, retrieve, reason, and act via APIs, all monitored through MRM and Eval Studio for accuracy, safety, and cost.
What it does
Built for data science leaders, ML engineers, MLOps teams, analytics translators, and enterprise developers who must operationalize GenAI alongside predictive models. It fits banks, telcos, and public‑sector organizations needing sovereign control, document‑heavy workflows, or 24/7 assistants for policy and procurement. Fraud teams, call‑center operations, risk and compliance, and IT operations benefit from agents that retrieve authoritative content, forecast impact, and trigger actions within existing systems.
- Deploy air‑gapped enterprise agents with multi‑model support and granular cost controls.
- Fine‑tune LLMs and SLMs in LLM Studio on private datasets, without code.
- Automate feature engineering and modeling with Driverless AI, complete with explainability reporting.
- Unlock OCR and document understanding using H2OVL Mississippi with enterprise connectors.
- Operationalize, monitor, and govern models via H2O MLOps, Feature Store, and policies.

Why H2O.ai
Who should use it
Start with a live demo, then deploy on premises, in an air‑gapped enclave, or within a cloud VPC. Use H2O LLM Studio to fine‑tune models on private corpora, or select Danube3 and other openweight options. Connect SharePoint, Google Drive, Slack, and Teams to supply enterprise context. Build task‑specific apps with H2O Wave or install from the GenAI App Store. Register models and datasets in H2O Feature Store, label with Label Genie, and push to production using H2O MLOps with canary or blue‑green rollout. Track cost, latency, quality, and safety with MRM and Eval Studio, and integrate actions through APIs.
Private generative and predictive AI that runs where your data lives.
Getting started
H2O.ai’s edge is the convergence of agentic GenAI, mature predictive ML, and rigorous governance in sovereign deployments. Openweight models, offline‑capable SLMs, and air‑gapped support reduce dependency risks. tabH2O simplifies tabular inference, and Driverless AI accelerates production modeling. The company reports leading accuracy on GAIA deep‑research benchmarks, and its platform is proven by regulated institutions—making it a pragmatic choice when trust, control, and operating cost matter.
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