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H2O.ai Stock (HTWO)
H2O.ai aims to remove the barriers to AI adoption. According to H2O.aim their open-source platform and enterprise solutions empower businesses of all sizes to leverage powerful machine learning – predictive analytics, generative AI – without needing an army of data scientists. This democratizes AI for industries like finance, healthcare, and retail
H2O.ai is a machine learning platform that builds smart applications.
About H2O.ai Stock
Founded
2011
Headquarters
Mountain View, CA, US
Total Funding
269M
Industries
Software, Data and Analytics, Science and Engineering
H2O.ai is a provider of a cloud-based open-source machine learning platform as well as enterprise AI solutions. The company's mission is to democratize AI for everyone by providing a set of tools that allows companies to build generative AI and predictive AI applications without the need for large teams of data scientists. H2O.ai's core product H2O-3, is an open-source machine learning platform that supports widely used statistical & machine learning algorithms. H2O.ai aims to empower every company to be an AI company in industries such as financial services, insurance, healthcare, and retail.
H2O.ai was founded in 2011 by Sri Ambati and Cliff Click and is headquartered in Mountain View, CA. Notable investors include Goldman Sachs, Celesta Capital, Paxion Capital Partners, and Wells Fargo.
H2O.ai Press Mentions
Stay in the know about the latest news on H2O.ai
Analytics and Data Science News for the Week of March 21; Updates from Anaconda, DataRobot, H2O.ai & More
solutionsreview • Mar 22, 2025
Explainable AI Market to USD 33.20 Billion by 2032| SNS Insider
globenewswire • Mar 21, 2025
12 New AI-Focused Technologies For Nvidia AI Ecosystem At Nvidia GTC 2025
crn • Mar 21, 2025
H2O.ai Launches Enterprise LLM Studio: Fine-Tuning-as-a-Service for Domain-Specific Models on Private Data
businesswire • Mar 13, 2025
The tech companies building AI guardrails for banks
americanbanker • Mar 06, 2025
Investors in H2O.ai
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H2O.ai Management
Leadership team at H2O.ai
Chief Executive Officer
Sri Ambati
Chief Technology Officer
Arno Candel
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H2O.ai Key Facts
• H2O.ai has established strategic partnerships with leading technology providers, cloud platforms, and consulting firms to expand its market reach and integration capabilities. Partnerships with companies like Microsoft Azure, IBM, and Nvidia enhance interoperability with cloud services and hardware accelerators, and thus, as H20.ai claimes, enable seamless deployment and performance optimization of AI models.
• H2O.ai actively contributes to the open-source community, fostering innovation and collaboration in AI and machine learning development. The company’s commitment to open-source projects such as H2O-3 and Driverless AI Community Edition enhances accessibility to advanced analytics capabilities and promotes knowledge sharing among data scientists and developers worldwide.
• Enterprises like PayPal and Progressive Insurance leverage H2O.ai’s technology to optimize customer experience, personalize marketing campaigns, and improve operational workflows. This enterprise adoption underscores H2O.ai’s market leadership and the value it delivers in driving digital transformation and innovation across industries.
• Its competitors include established players such as Google (with TensorFlow), Facebook (with PyTorch), and Microsoft (with Azure ML), as well as a growing number of startups offering specialized AI solutions. These competitors have significant resources, extensive research capabilities, and established market presence, which could pose challenges to H2O.ai’s market expansion and customer acquisition efforts.
• H2O.ai’s revenue is closely tied to enterprise adoption of AI and machine learning solutions, which are subject to fluctuations in corporate spending, economic cycles, and technological trends. During periods of economic uncertainty or reduced corporate budgets, businesses may prioritize cost-cutting measures, including reductions in AI investments and technology upgrades.
• H2O.ai operates in a regulatory environment characterized by evolving compliance requirements, and ethical considerations related to AI and machine learning applications. Ensuring compliance with regulations such as GDPR and CCPA requires ongoing investment in data governance practices, security measures, and transparency in AI model development and deployment.
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