List of H2O.ai Customers
Mountain View, 94043, CA,
United States
Since 2010, our global team of researchers has been studying H2O.ai customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased H2O.ai for ML and Data Science Platforms from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using H2O.ai for ML and Data Science Platforms include: AT&T, a United States based Communications organisation with 146040 employees and revenues of $122.43 billion, National Institutes of Health, a United States based Government organisation with 18478 employees and revenues of $45.18 billion, CommBank, a Australia based Banking and Financial Services organisation with 48580 employees and revenues of $18.66 billion and many others.
Contact us if you need a completed and verified list of companies using H2O.ai, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The H2O.ai customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
Apply Filters For Customers
| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
|---|---|---|---|---|---|---|---|---|---|---|---|
 |
AT&T | Communications | 146040 | $122.4B | United States | H2O.ai | H2O.ai | ML and Data Science Platforms | 2021 | n/a |
In 2021, AT&T implemented H2O.ai as an AI-as-a-Service platform using H2O AI Cloud to operationalize machine learning across customer-facing and network functions. This deployment situates H2O.ai squarely within the ML and Data Science Platforms category to address fraud prevention, predictive maintenance and call-center optimization.
The implementation co-created with H2O.ai includes the H2O AI Feature Store, Driverless AI and MLOps capabilities, forming a platform architecture that moves models from prototype to production. These modules provide feature management, automated model development and lifecycle orchestration consistent with ML and Data Science Platforms functional workflows.
Operational scope explicitly spans marketing, network operations and customer service within the United States, with business functions impacted including fraud detection, predictive maintenance for network assets and call-center analytics. The H2O.ai deployment functions as an enterprise AI-as-a-Service layer to provision models and serve predictions to those operational teams.
Governance and process changes centered on operationalizing ML through MLOps pipelines and feature governance via the H2O AI Feature Store, standardizing model promotion and production monitoring. The program delivered explicit outcomes including greater than 80% reduction in iPhone fraud and multi-million dollar annual savings.
|
 |
CommBank | Banking and Financial Services | 48580 | $18.7B | Australia | H2O.ai | H2O.ai | ML and Data Science Platforms | 2021 | n/a |
In 2021, CommBank implemented H2O.ai within the ML and Data Science Platforms category to deploy generative AI and predictive machine learning capabilities across fraud detection, customer service, and personalization. The initiative scaled across dozens of teams and moved more than 1,000 models into production across Australia, signaling an enterprise level machine learning program supporting both customer facing and risk workflows. H2O.ai was delivered using category aligned components, with public materials indicating use of H2O AI Cloud, Driverless AI and GenAI tooling to automate feature engineering, automated model development and model orchestration. The implementation included model training pipelines, automated scoring and inference endpoints, and operational monitoring to support continuous model iteration. Operational coverage focused on fraud risk scoring, scam detection and mitigation, contact center augmentation and personalized customer offers, with models embedded into decisioning and customer engagement flows across related business functions. Governance was structured to manage model lifecycle and deployment workflows, with data science and risk teams coordinating staging, validation and production promotion, and H2O.ai reporting outcomes that include large scale reductions in scam losses up to approximately 70 percent as part of the program.
|
 |
National Institutes of Health | Government | 18478 | $45.2B | United States | H2O.ai | H2O.ai | ML and Data Science Platforms | 2025 | n/a |
In 2025, the National Institutes of Health deployed H2O.ai as an ML and Data Science Platforms implementation to power an intranet Business Assistant managed by the Office of Business Systems. The deployment serves approximately 8,000 employees and operates across all 28 NIH institutes, supporting IT and internal support workflows, procurement search, and policy search while handling high volume service interactions.
The implementation uses H2O.ai’s h2oGPTe to deliver grounded responses with source attribution, enabling the Business Assistant to surface authoritative references for procurement and policy inquiries. Functional capabilities implemented include natural language understanding for enterprise queries, retrieval augmented generation aligned to internal document sources, and conversational routing for IT and service request triage.
The architecture is a sovereign, air gapped Oracle Cloud Isolated Region deployment, reflecting U.S. federal security and data residency requirements for internal support tooling. The air gapped Oracle Cloud Isolated Region hosts model inference and retrieval layers, while the intranet Business Assistant interfaces with NIH internal networks to provide query responses without external network egress.
Governance is centered on source attribution and controlled operational scope, with the Office of Business Systems operating the system across NIH institutes and defining use cases limited to IT support, procurement, and policy search. The deployment explicitly reports deflecting up to 10,000 IT and service requests annually, positioning H2O.ai and h2oGPTe within NIH’s ML and Data Science Platforms footprint for enterprise knowledge management and support automation.
|
Buyer Intent: Companies Evaluating H2O.ai
- MathWorks, a United States based Professional Services organization with 6000 Employees
Discover Software Buyers actively Evaluating Enterprise Applications
| Logo | Company | Industry | Employees | Revenue | Country | Evaluated | ||
|---|---|---|---|---|---|---|---|---|
| No data found | ||||||||