List of H2O Wave Customers
Mountain View, 94043, CA,
United States
Since 2010, our global team of researchers has been studying H2O Wave 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 Wave 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 Wave for ML and Data Science Platforms include: AT&T, a United States based Communications organisation with 146040 employees and revenues of $122.43 billion, Kaiser Foundation Health Plan, a United States based Healthcare organisation with 223883 employees and revenues of $100.80 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 Wave, 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 Wave 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 Wave | ML and Data Science Platforms | 2021 | n/a |
In 2021, AT&T partnered with H2O.ai to deploy H2O Wave as part of an AI-as-a-Service capability. H2O Wave was implemented within the ML and Data Science Platforms category to build real-time AI applications focused on fraud detection and customer experience across the United States, and the program emphasized democratizing AI across AT&T's data teams.
The implementation leveraged H2O Wave's real-time application framework together with feature-store capabilities and model serving to enable real-time scoring. The initiative placed hundreds of models into production and established production model workflows and feature management to support low-latency inference for operational use cases, reflecting core ML and Data Science Platforms functions such as model deployment, feature engineering, and online scoring.
Operational ownership was organized as a centralized AI-as-a-Service capability that provisioned self-service access for data scientists and product teams, while usage extended across business functions including fraud detection and customer experience analytics. Rollout and governance prioritized standardized model production pipelines and feature-store access to streamline scoring workflows, and the vendor announcement framed these elements as enabling production scale and broader AI access across AT&T rather than quantifying specific performance outcomes.
|
 |
CommBank | Banking and Financial Services | 48580 | $18.7B | Australia | H2O.ai | H2O Wave | ML and Data Science Platforms | 2021 | n/a |
In 2021, CommBank deployed H2O Wave as part of a strategic rollout with H2O.ai to embed ML and AI capabilities across core banking workflows. The deployment explicitly used H2O Wave within the bank's broader H2O.ai platform footprint to operationalize real-time machine learning and application-layer interfaces for banking use cases.
The implementation concentrated on three functional capabilities, real-time fraud detection, document processing for KYC, and AI-driven customer engagement. H2O Wave was used to construct real-time applications and operational dashboards that expose model inference and scoring, while the underlying H2O.ai platform supplied model training and production model serving for those use cases.
Integrations focused on embedding model inference into existing fraud detection pipelines, routing KYC document processing through AI-powered extraction and classification, and surfacing personalized engagement workflows to customer-facing channels. Operational coverage spanned Australian banking processes, touching fraud operations, KYC/AML processing, and customer service functions.
Governance followed a strategic partnership model with H2O.ai and the implementation was reported as large-scale production usage across the bank. The deployment delivered notable outcomes, with the bank reporting about a 70% reduction in scam losses attributed to the H2O.ai platform and its H2O Wave applications.
|
 |
Kaiser Foundation Health Plan | Healthcare | 223883 | $100.8B | United States | H2O.ai | H2O Wave | ML and Data Science Platforms | 2018 | n/a |
In 2018, Kaiser Foundation Health Plan built predictive clinical workflows using H2O.ai tools to create an Advanced Alert Monitoring capability aimed at identifying patient deterioration in the United States. H2O Wave is inferred as the application used from the ML and Data Science Platforms suite to prototype clinician-facing dashboards and operational apps that surfaced early-warning scores into bedside workflows.
The implementation combined predictive model development with rapid application prototyping, producing early-warning scores and clinician dashboards that translated model outputs into actionable alerts. H2O Wave is described in the context of the ML and Data Science Platforms deployment as the front-end prototyping and app framework, while the overall solution included model scoring and rules to generate time-series risk signals for ICU care teams.
Operational coverage focused on ICU clinical workflows and acute care teams, where the early-warning scores were integrated into clinician decision paths to prompt intervention. The project is described as improving ICU intervention and clinical outcomes, with governance centered on embedding risk scores into operational workflows and clinician-facing apps for real-time use.
|
Buyer Intent: Companies Evaluating H2O Wave
Discover Software Buyers actively Evaluating Enterprise Applications
| Logo | Company | Industry | Employees | Revenue | Country | Evaluated | ||
|---|---|---|---|---|---|---|---|---|
| No data found | ||||||||