H20.ai, a purveyor of artificial intelligence (AI) solutions, has garnered attention from the investor community. On November 8, 2021, the company announced a $100 million Series E fundraise, led by one of their customers, Commonwealth Bank of Australia.
H2O’s core offering is an end-to-end data science platform, but they also provide a series of open-source solutions that aid in a company’s AI deployment.
H20's open-source AI solutions:
- H2O Wave, an open-source Python development framework for developing real-time interactive AI apps
- H2O AutoML, which allows for the training and evaluation of machine learning models
- Sparkling Water, for combining the fast, scalable machine learning algorithms of H2O with the capabilities of Spark
G2 data indicates a growing AI trend
H2O is also well-liked by their customers on G2 and was rated a High Performer on G2's Fall 2021 Data Science and Machine Learning Platforms Grid Report.
G2 reviewers appreciate H2O’s open-source components, with one reviewer noting that “they developed top-quality open source tools.” Great open source solutions can only succeed with a strong and supportive community and resources around them. Therefore, it is key to note that reviewers appreciated H2O’s efforts in creating these resources. The aforementioned reviewer remarked that ”their learning center is shaping up as a valuable resource to the community.”
Looking at their core H2O offering, the majority of their reviews on G2 have come from small businesses. This aligns with the general trend across G2's Artificial Intelligence categories, as can be seen below in Figure 1. We have even seen an increase in the percentage of reviewers coming from small businesses reviewing AI products on G2.
Figure 1: Percentage of Small Business Reviewers of AI Products in on the Rise
A common refrain that has made its rounds in the media is that “AI is for larger companies”. Although smaller companies might struggle with some components of AI development (such as amassing large datasets to train algorithms and having the resources to hire data scientists), the refrain is not accurate.
If we cautiously translate the percentage of small business reviewers of AI solutions into overall users of AI solutions, we would conclude that well over 50% of users are coming from small businesses.
This will likely increase, with the following trends:
Data augmentation solutions
Last year, G2 added a synthetic data software category, which has been steadily increasing in popularity in terms of reviews and traffic (seeing a 111% traffic increase in September 2021). Synthetic data is one of a series of solutions that can be used to augment and supplement existing datasets. Besides the privacy benefits, it can help boost and bolster smaller datasets to have a more robust dataset for training algorithms. In addition, data science platforms that allow users to supplement their data with relevant data (e.g., industry data), such as Explorium, can help them create proprietary datasets.
Data scientists are expensive. According to O’Reilly’s 2021 Data/AI Salary Survey, the average salary for data and AI professionals was $146,000. For small companies that don’t have that kind of money, low-code solutions, such as Pecan, can help them get a leg up. With these tools, developers and product managers can imbue their applications, websites, and more with the benefits of (often pre-built) algorithms without the need to hire an entire data science team.
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