H2O.ai
Founded Year
2011Stage
Series E | AliveTotal Raised
$246.12MValuation
$0000Last Raised
$100M | 2 yrs agoAbout H2O.ai
H2O.ai delivers an advanced artificial intelligence (AI) cloud platform. It helps to solve complex business problems and accelerates the discovery of new ideas. The company makes machine learning accessible to corporates and allows business users to extract key information from data with deployments in financial services, government, health, insurance, manufacturing, and other industries. It was formerly known as 0xdata. The company was founded in 2011 and is based in Mountain View, California.
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ESPs containing H2O.ai
The ESP matrix leverages data and analyst insight to identify and rank leading companies in a given technology landscape.
The AI development platforms market offers a range of solutions to help organizations build and integrate AI-powered solutions to deliver on commercial objectives. These platforms address common obstacles faced by organizations, such as siloed and messy data, slow decision-making despite having more data available, and difficulty in productionizing AI projects. The platforms also offer capabilitie…
H2O.ai named as Outperformer among 15 other companies, including Databricks, Dataiku, and Hugging Face.
Research containing H2O.ai
Get data-driven expert analysis from the CB Insights Intelligence Unit.
CB Insights Intelligence Analysts have mentioned H2O.ai in 8 CB Insights research briefs, most recently on May 10, 2023.
Expert Collections containing H2O.ai
Expert Collections are analyst-curated lists that highlight the companies you need to know in the most important technology spaces.
H2O.ai is included in 7 Expert Collections, including Unicorns- Billion Dollar Startups.
Unicorns- Billion Dollar Startups
1,227 items
Regtech
1,453 items
Technology that addresses regulatory challenges and facilitates the delivery of compliance requirements. Regulatory technology helps companies and regulators address challenges ranging from compliance (e.g. AML/KYC) automation and improved risk management.
AI 100
200 items
Insurtech
4,131 items
Companies and startups that use of technology to improve core and ancillary insurance operations. Companies in this collection are creating new product architectures, improving underwriting models, accelerating claims and creating a better customer experience
Artificial Intelligence
10,944 items
Companies developing artificial intelligence solutions, including cross-industry applications, industry-specific products, and AI infrastructure solutions.
Conference Exhibitors
5,302 items
H2O.ai Patents
H2O.ai has filed 9 patents.
The 3 most popular patent topics include:
- Machine learning
- Classification algorithms
- Artificial intelligence
Application Date | Grant Date | Title | Related Topics | Status |
|---|---|---|---|---|
1/31/2019 | 5/30/2023 | Machine learning, Statistical classification, Computer security, Computer network security, Classification algorithms | Grant |
Application Date | 1/31/2019 |
|---|---|
Grant Date | 5/30/2023 |
Title | |
Related Topics | Machine learning, Statistical classification, Computer security, Computer network security, Classification algorithms |
Status | Grant |
Latest H2O.ai News
Sep 11, 2023
Market Dynamics Drivers 1. Rising Labor Costs and Workforce Challenges: The escalating labor costs and the challenges associated with the availability of a skilled workforce, especially in regions like North America and Europe, have become a driving force for the adoption of robot software. As businesses seek cost-effective alternatives to human labor, robot software offers a solution that is reliable, efficient, and doesn't require benefits or breaks. This factor is fueling the demand for software-equipped robots to perform tasks with precision, consistency, and cost-effectiveness. 2. Industry 4.0 and IoT Integration: The emergence of Industry 4.0 and the integration of the Internet of Things (IoT) are transforming industries by digitizing and automating processes. Robot software plays a pivotal role in this transformation by enabling seamless communication and coordination between machines, automation systems, and data analytics platforms. This integration enhances production efficiency, enables predictive maintenance, and optimizes operations, all of which contribute to the growing demand for advanced robot software. Restraints 1. Cybersecurity and Data Protection Concerns: The adoption of robot software raises concerns about cybersecurity and data protection. As robots become interconnected and data-driven, they become vulnerable to cyberattacks and unauthorized access. Ensuring the security and privacy of sensitive data transmitted and stored by robot software solutions is a significant challenge that the industry must address to foster wider adoption. 2. High Development and Implementation Costs: Creating and deploying sophisticated robot software solutions demands substantial financial resources. The high costs involve skilled engineering talent, hardware and sensor procurement, rigorous testing, and customization to industry-specific requirements. These barriers can hinder smaller businesses and startups from entering the market or investing in advanced robot software solutions. Opportunities 1. Robotics-as-a-Service (RaaS) Model: The Robotics-as-a-Service (RaaS) model is transforming the robot software market. By offering a subscription-based approach, RaaS eliminates the need for substantial upfront investments, making advanced robot solutions accessible to businesses of all sizes. This model provides flexibility, scalability, ongoing support, and access to the latest technologies, particularly beneficial for small and medium enterprises (SMEs) looking to leverage robot software capabilities. 2. Technological Innovation and Collaboration: The ongoing advancements in robotics technology, artificial intelligence (AI), and machine learning are opening new avenues for innovation in robot software. Collaborations between software developers, robotics manufacturers, and industries are driving the creation of cutting-edge solutions that cater to specific industry needs, promoting the adoption of advanced robot software. 3. Expansion of Use Cases: The adoption of robot software is extending beyond traditional manufacturing sectors. Industries such as healthcare, logistics, retail, and entertainment are increasingly recognizing the potential of robot software to enhance efficiency, reduce costs, and deliver unique customer experiences. This expansion of use cases broadens the market's scope and offers new growth opportunities. Segmentation The global robot software market is segmented based on software type, robot type, deployment mode, organization size, industry vertical, and geography. The North American region is anticipated to dominate the market by 2030 due to its diverse industries and significant investments in R&D activities that foster innovation and technological advancements. Competitive Profile: Notable players in the robot software industry include IBM, NVIDIA, ABB Ltd., FANUC, Teradyne, H2O.ai, Brain Corp, CloudMinds, Clearpath Robotics, and Neurala, Inc. Recent developments in the market include the introduction of advanced platforms such as H2O GPT LLM Studio by H2O.ai, the merger of AutoGuide Mobile Robots and Mobile Industrial Robots (MiR) by Teradyne, the launch of Outdoor Autonomy Software by Clearpath Robotics, the establishment of a robotics facility by FANUC, and ABB's acquisition of ASTI Mobile Robotics Group. In conclusion, the Robot Software Market is driven by a combination of factors including the need to mitigate rising labor costs, the transformative impact of Industry 4.0 and IoT, and the potential of Robotics-as-a-Service. While cybersecurity concerns and high development costs present challenges, technological innovation and the diversification of use cases promise significant opportunities for growth and advancement in the industry. The robot software market report offers quantitative analysis, trends assessment, drivers and restraints analysis, competitive analysis, and value chain analysis. The report provides a comprehensive understanding of prevailing market opportunities, trends, and the impact of key drivers and restraints. For more information about this report visit https://www.researchandmarkets.com/r/8fr7rc About ResearchAndMarkets.com ResearchAndMarkets.com is the world's leading source for international market research reports and market data. We provide you with the latest data on international and regional markets, key industries, the top companies, new products and the latest trends. Tags Contact Data CONTACT: ResearchAndMarkets.comLaura Wood,Senior Press Managerpress@researchandmarkets.comFor E.S.T Office Hours Call 1-917-300-0470For U.S./ CAN Toll Free Call 1-800-526-8630For GMT Office Hours Call +353-1-416-8900
H2O.ai Frequently Asked Questions (FAQ)
When was H2O.ai founded?
H2O.ai was founded in 2011.
Where is H2O.ai's headquarters?
H2O.ai's headquarters is located at 2307 Leghorn Street, Mountain View.
What is H2O.ai's latest funding round?
H2O.ai's latest funding round is Series E.
How much did H2O.ai raise?
H2O.ai raised a total of $246.12M.
Who are the investors of H2O.ai?
Investors of H2O.ai include NVIDIA, Wells Fargo Strategic Capital, Crane Venture Partners, Celesta Capital, New York Life Insurance Company and 18 more.
Who are H2O.ai's competitors?
Competitors of H2O.ai include Fiddler AI, Predibase, DataRobot, TurinTech, Dataiku, Cognida, Katonic, CognitiveScale, Xpanse, Atidot and 35 more.
- Predict emerging trends
- See competitors' playbooks
- Stalk the smart money
- Identify tomorrow's challengers
- Spot growing industries
- Kill analyst data work
Compare H2O.ai to Competitors
DataRobot operates as an artificial intelligence (AI) lifecycle platform with ecosystem integrations. It offers solutions such as augmented intelligence, data engineering, machine learning, artificial intelligence, and more and serves the banking, healthcare, retail, manufacturing, and public sectors. The company was founded in 2012 and is based in Boston, Massachusetts.
Dataiku develops a centralized data platform to help businesses in their data journey from analytics at scale to enterprise artificial intelligence (AI). Its solutions include data preparation, visualization, machine learning, analytic applications, and more. The company serves the banking sector, pharmaceuticals, manufacturing telecommunication sector, and more. It was founded in 2013 and is based in New York, New York.
BigML offers a cloud-based machine learning (ML) service to enable smart business analytics. Through the company's interface users analyze their data and build predictive models. It was founded in 2011 and is based in Corvallis, Oregon.
Peak is a data analytics-as-a-service company. It helps businesses with data services using artificial intelligence and machine learning technologies. It was founded in 2015 and is based in Manchester, United Kingdom.
Databricks provides a unified analytics platform. It offers a collaborative solution for the machine learning lifecycle such as featurization production and also provides data analytic services to simplify data integration. It serves financial services, healthcare and life sciences, manufacturing, communications, media and entertainment, and public sector. Databricks was founded in 2013 and is based in San Francisco, California.
Seldon Technologies builds global infrastructure for machine learning (ML) operations. It accelerates the adoption of machine learning to improve business performance and manage risk. It enables data scientists to speed up the process of data interpretation. It was founded in 2014 and is based in London, United Kingdom.
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