AI and machine learning can be complicated for a layperson to fully grasp, yet surveys show this hasn’t deterred enterprises from adopting the technology in droves. Business use of AI grew a whopping 270% over the past four years, according to Gartner, while Deloitte says 62% of respondents to its corporate October 2018 report deployed some form of AI, up from 53% a year ago.

But adoption doesn’t always meet with success, as the roughly 25% of companies who’ve seen half of their AI projects fail will tell you. That’s why managed machine learning solutions firms like H2O.ai are growing at a healthy clip. Indeed, more than 200,000 data scientists and over 18,000 organizations, including Aetna, Booking.com, Comcast, Hitachi, Nationwide Insurance, PwC, and Walgreens, actively use H2O’s data science tools. In perhaps another sign of the industry’s upward momentum, H2O today announced that it has raised $72.5 million in a round led by Goldman Sachs and the Ping An Global Voyager fund, with continued investments from Wells Fargo and Nexus Venture Partners.

Jade Mandel from Goldman Sachs will join H2O’s board of directors as part of the round, which brings the Mountain View, California-based company’s total raised to $147 million. This follows a $20 million series B raised in November 2015 and a $40 million series C in November 2017. It also comes after H2O tripled its customer base and increased its data scientist headcount by 10%.

H2O founder and CEO Sri Ambati said the capital will accelerate the company’s global sales, R&D, and marketing efforts. He also expects it to bolster H2O’s ongoing AI for good initiatives (with a focus on wildlife and water conservation) along with its academic programs and AI centers of excellent that afford students, researchers, and universities free access to its product portfolio.

“H2O.ai is democratizing AI and powering the imagination of every entrepreneur and business globally — we are making them the true AI superpowers,” said Ambati. “Our customers are unlocking discovery in every sphere and walk of life and challenging the dominance of technology giants. This will be fun.”

H2O

Above: H2O’s driverless AI platform.

Image Credit: H2O

For the uninitiated, H2O was founded in 2012 by Ambati, who previously served as a research assistant at the Indian Space Research Organization. H2O’s suite of solutions is designed to simplify machine learning deployment at scale across verticals like financial services, insurance, health care, telecommunications, retail, pharmaceutical, and marketing, with applications in customer churn prediction, credit risk scoring, and more.

H2O’s eponymous flagship product is an AI platform that runs on bare metal or atop existing clusters and supports a range of statistical models and algorithms. Its AutoML functionality automatically runs through models and their hyperparameters to produce a leaderboard of the best models, taking advantage of the computing power of distributed systems and in-memory computing to accelerate data processing and model training. According to H2O, it’s able to ingest data directly from HDFS, Spark, S3, Azure Data Lake, or virtually any other local or cloud data source.

H2O’s Sparkling Water marries H2O with Spark, Apache’s distributed cluster computing framework, by initializing H2O services on Spark and providing a way to access data stored in Spark and H2O data structures. As for H2O’s H2OGPU, it’s a GPU-accelerated AI package with APIs in Python and R that enables users to tap graphics cards for accelerated machine learning model development.

Then there’s H2O Driverless AI, an “automatic” AI solution that guides customers through the process of creating their own AI-imbued apps and services. The latest version, which was released today, adds the ability to create recipes that extend and customize the platform, in addition to administration and collaboration features for model management and implementation and new explainable AI capabilities for fairness and bias checks.

Among the Driverless AI features debuting this week are health checks and data science metrics around drift detection, model degradation, A/B testing, and alerts for recalibration and retraining. In addition, the platform can now perform disparate impact analysis to test for sociological biases in models, allowing users to analyze whether a model produces adverse outcomes for different demographic groups even if those features were not included in the original model.

The first set of vertical-specific Driverless AI solutions making their debut target anti-money laundering, customer monitoring, and malicious domain detection. Over 100 open source recipes curated by top achievers on Google’s Kaggle community are also available, all of which feed into an interactive dashboard that explains their outputs in plain English.

For customers with highly specific deployment requirements, H2O offers enterprise support with training, dedicated account managers, accelerated issue resolution, and direct enhancement requests. Plans also include access to Enterprise Steam or H2O Sparkling Water for the orchestration of machine learning models in Hadoop or Spark clusters.

“We have been a big believer in H2O.ai since day one. We are ecstatic to see their success across the world with so many companies, in so many industries,” said Nexus Venture Partners managing director Jishnu Bhattacharjee in a statement. “AI in the enterprise is a reality that H2O.ai is driving. We are thrilled to continue backing Sri and team as they accelerate their growth trajectory.”

The lengthy list of H2O’s existing and previous investors includes Barclays, Capital One, Crane Ventures, CreditEase, New York Life, Nvidia, Paxion Ventures, SST Holdings, TransAmerica, and Walden River Wood. H2O has offices in New York and Prague, in addition to its Mountain View headquarters.

Sign up for Funding Daily: Get the latest news in your inbox every weekday.