H2O.ai Launches Deep Water, Deep Learning for Enterprise

Deep Water provides Fortune 500 enterprises with GPU-powered Deep Learning platform to analyze unstructured data like images, video, text and audio

MOUNTAIN VIEW, Calif.--()--H2O.ai, the company bringing AI to business, last month announced the release of its Deep Water product, a GPU-powered deep learning offering that’s giving Fortune 500 companies the ability to optimize business operations by analyzing and processing massive amounts of unstructured data, such as images, video, text and audio, at a much faster rate. Deep Water integrates GPU backends TensorFlow, MXNet and Caffe for broad adoption and ease of use.

Most enterprise businesses have been blindsided by the unprecedented amount of data that’s materialized over the past decade. Deep Water ingests these enormous data sets and simplifies tasks for portfolio managers, claims adjusters, doctors and more. The tool’s unmatched computational power and predictive abilities fully automate processes like credit scoring and disease diagnosis. Other use cases include:

  • Credit Risk and Lending - Redefine credit assessment using non-traditional data gathered through social media and instant loan approval with data analytics.
  • Preventative Maintenance - Analyze images of homes and other property and provide insights on how to protect from potential damages.
  • X-Ray Diagnosis - Automatically predict likelihood of specific diseases and ailments using x-ray scans.
  • Predictive IT Traffic - Pattern analysis and prediction for Distributed Denial of Service (DDoS) detection and prevention and predictive maintenance of data center equipment.

“Every enterprise needs a google brain and H2O.ai is making it possible,” said SriSatish Ambati, co-founder and CEO of H2O.ai. “The release of Deep Water is a landmark moment that finally introduces enterprise organizations to scalable predictive models and GPUs to automate day-to-day processes in fintech, healthcare, insurance and other verticals.”

From a technical perspective, Deep Water’s multipronged solution bundles H2O's familiar interfaces from Python, R and H2O’s graphical UI (Flow) with the most popular deep learning GPU backends: TensorFlow, MXNet and Caffe. Moving forward, H2O.ai will continue to make Deep Water and its other tools even more automated using data from its enterprise customers, and its own community of open source users.

H2O.ai launched in 2011 with the goal of democratizing data science by making open-source deep learning accessible to everyone. Its premiere product, H2O, features the fastest distributed data ingest and data munging capabilities, and a multitude of enterprise features such as security, authentication, model comparison and rapid deployment. Today, H2O is used by more than 9,000+ organizations and 80,000+ data scientists from all over the world.

To find out more about Deep Water please visit http://www.h2o.ai/deep-water/.

About H2O.ai

H2O.ai is focused on bringing AI to businesses through software. Its flagship product is H2O, the leading open source deep learning platform that makes it easy for financial services, insurance and healthcare companies to deploy AI and deep learning to solve complex problems. More than 9,000+ organizations and 80,000+ data scientists depend on H2O for critical applications like predictive maintenance and operational intelligence. The company -- which was recently named to the CB Insights AI 100 -- is used by 107 Fortune 500 enterprises, including 8 of the world’s 10 largest banks, 7 of the 10 largest insurance companies and 4 of the top 10 healthcare companies. Notable customers include Capital One, Progressive Insurance, Transamerica, Comcast, Nielsen Catalina Solutions, Macy’s, Walgreens, Kaiser Permanente, and Aetna.

Follow us on Twitter @h2oai. To learn more about H2O customer use cases, please visit http://www.h2o.ai/customers/ Join the Movement.

Contacts

VSC for H2O.ai
James Christopherson
Senior Account Manager
james@vscpr.com

Contacts

VSC for H2O.ai
James Christopherson
Senior Account Manager
james@vscpr.com