List of H2O Driverless AI Customers
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United States
Since 2010, our global team of researchers has been studying H2O Driverless 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 Driverless 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 Driverless AI for ML and Data Science Platforms include: PayPal, a United States based Banking and Financial Services organisation with 24400 employees and revenues of $31.80 billion, Stanley Black & Decker, a United States based Manufacturing organisation with 50000 employees and revenues of $15.78 billion, Xceedance, a United States based Professional Services organisation with 3500 employees and revenues of $500.0 million, G5, a United States based Professional Services organisation with 250 employees and revenues of $50.0 million, Reproductive Science Center of the SF Bay Area, a United States based Healthcare organisation with 50 employees and revenues of $5.0 million and many others.
Contact us if you need a completed and verified list of companies using H2O Driverless 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 Machine Learning software purchases.
The H2O Driverless 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 Machine Learning software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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G5 | Professional Services | 250 | $50M | United States | H2O.ai | H2O Driverless AI | ML and Data Science Platforms | 2016 | n/a |
In 2016, G5 implemented H2O Driverless AI in partnership with H2O.ai to power its Intelligent Marketing Cloud, embedding ML and Data Science Platforms capabilities into core marketing workflows. G5 implemented H2O Driverless AI as an ML and Data Science Platforms solution to support marketing and lead prioritization functions across the property management marketplace.
The implementation centered on automated machine learning capabilities native to H2O Driverless AI, including automated feature engineering, model selection and validation, model interpretability and production scoring. The G5 data science team configured end to end modeling pipelines inside H2O Driverless AI, generating lead propensity scores and model explainability artifacts for use by downstream campaign systems.
H2O Driverless AI was integrated into the Intelligent Marketing Cloud to operationalize real time and batch scoring for inbound leads, enabling prioritized lead routing and campaign-level spend allocation. Operational scope included marketing, demand generation and sales use cases within G5 customer deployments in the property management marketplace, with models feeding campaign workflows and lead management systems.
Governance and rollout were led by the G5 data science organization, which implemented model validation, monitoring and explainability controls to support decisioning in campaign orchestration. The deployment is positioned to prioritize inbound leads to drive conversions and to reduce digital marketing spend as stated in the implementation notes.
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PayPal | Banking and Financial Services | 24400 | $31.8B | United States | H2O.ai | H2O Driverless AI | ML and Data Science Platforms | 2017 | n/a |
In 2017, PayPal implemented H2O Driverless AI to augment its fraud modeling workflows. The deployment leveraged H2O Driverless AI as part of the companys ML and Data Science Platforms layer to accelerate automated feature engineering and model building for fraud detection use cases.
The PayPal data science team, which had more than 10 years of feature engineering experience on the fraud problem, used H2O Driverless AI to surface significant new modelling features. H2O Driverless AI produced a nearly 6 percent increase in model accuracy in a single test, demonstrating the platform's automated feature discovery and model experimentation capabilities when applied to mature fraud datasets.
Operationally the implementation focused on embedding H2O Driverless AI into existing fraud detection workflows, augmenting experienced feature engineers rather than replacing them, and informing ongoing model development and scoring pipelines. PayPal plans to continue using H2O Driverless AI to prevent fraudulent activities, indicating an ongoing operational commitment within its fraud prevention business function.
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Reproductive Science Center of the SF Bay Area | Healthcare | 50 | $5M | United States | H2O.ai | H2O Driverless AI | ML and Data Science Platforms | 2016 | n/a |
In 2016, Reproductive Science Center of the SF Bay Area implemented H2O Driverless AI. The deployment positioned H2O Driverless AI within ML and Data Science Platforms to support IVF laboratory research and predictive modeling for the clinic's research function.
The implementation leveraged automated feature engineering, automated model selection, and model interpretability capabilities typical of H2O Driverless AI to accelerate exploratory model development for a small research team. The platform surfaced engineered feature combinations that extended domain expertise and supported model scoring and validation workflows used by lab researchers.
Operational scope centered on the IVF laboratory research department, where the Research Director Oleksii Barash led adoption and day to day use. H2O Driverless AI produced candidate models and engineered features for validation and downstream research analysis, enabling the lab to iterate on predictive use cases within clinical research workflows.
Governance was researcher led, with the lab team managing model evaluation and decisions about experimental deployment into research processes. As stated by Oleksii Barash, IVF Laboratory Research Director, Driverless AI is awesome, the feature engineering creates combinations that I would never think of even with my domain knowledge, highlighting the platform's role in expanding hypothesis generation through automated feature construction.
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Manufacturing | 50000 | $15.8B | United States | H2O.ai | H2O Driverless AI | ML and Data Science Platforms | 2016 | n/a |
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Professional Services | 3500 | $500M | United States | H2O.ai | H2O Driverless AI | ML and Data Science Platforms | 2017 | n/a |
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