Datagran is raising a Crowd SAFE at a $27 million valuation with no discount. This valuation is justified given Datagran’s sizable revenue and the company’s highly technical, patent-pending software platform. On the revenue side, Datagran generated $1.9 million in income for 2020 (the most recent financials available). That figure implies a 14.4x revenue-to-valuation multiple, which is reasonable for a machine-learning software business. Datagran’s platform also has a great deal of intrinsic value, given five years of development, a differentiated value proposition, and a pending patent. Investors are getting a reasonable deal on this opportunity.

Datagran provides a cloud-based software-as-a-service tool that enables machine learning — in other words, machine learning as a service. There’s a growing demand for such tools. The machine-learning-as-a-service (MLaaS) market was valued at nearly $3 billion globally in 2021 and is expected to grow rapidly to $21.8 billion in 2028 with a 39.5% compound annual growth rate. MLaaS is one niche within the broader machine-learning market, which is estimated to reach $152.2 billion globally by 2028.

At present, the MLaaS market is still relatively small. Most businesses haven’t yet developed advanced data analysis capabilities. However, the growth outlook for this market is very optimistic. As machine learning becomes more prevalent and less intimidating for the average professional, more companies will see the value in activating machine learning to uncover key strategic insights. Datagran has the opportunity to lead the rapid adoption of machine learning tools within this growing market. 

Datagran is led by founder and CEO Carlos Méndez. Méndez spent most of his career in advertising, with more than 20 years of experience at different agencies (including an agency of his own, which was reportedly one of Colombia’s top 20 advertising agencies). Méndez eventually pivoted from advertising to computer science and machine learning. He is now working toward a master’s in software engineering at Harvard University. Méndez is leveraging his career as a marketing decision-maker combined with his recent ventures into software and machine learning to create a data tool that is useful for non-technical stakeholders. 

The Datagran team also includes CTO Necati Demir. Demir holds a PhD in computer science, specifically in the “modified stacking ensemble approach for network intrusion detection,” from Dokuz Eylul University in Turkey. Demir has more than 15 years of experience as a software developer, technical manager, and security consultant. 

The Datagran executive team combines business and marketing experience with deep technical expertise, which is ideal for a highly technical company attempting to market itself toward less sophisticated data practitioners. The team certainly needs to grow and incorporate additional disciplines, particularly sales and finance, as Datagran grows. For now, though, Datagran is led by a competent team.

Datagran’s core pitch is making machine learning more accessible for businesses of all shapes and sizes. Machine learning can be a highly technical, confusing and inaccessible topic for most professionals. Employees at small and medium-sized businesses likely think that machine learning is far beyond their capabilities. However, Datagran offers a self-serve platform where anyone can explore what it’s like to connect multiple data sources, visualize that data, and use it to make decisions. That quick setup time and ability to integrate with countless business tools are key differentiators for Datagran. 

Datagran is positioning itself as the Zapier of machine learning. Five or 10 years ago, a no-code automation tool like Zapier seemed beyond the reach of many business owners. But these days, Zapier is a well-regarded and relatively easy way to automate repetitive business processes. If Datagran can transform machine learning into an accessible, high-leverage tool for companies of all sizes, it could replicate Zapier’s smashing success.

Datagran has outperformed on most key performance indicators. After its founding in 2017, the company’s revenue skyrocketed to $2.7 million in 2019. Revenue suffered a decline in 2020, likely due to the pandemic, but Datagran still brought in $1.9 million. Additionally, Datagran’s cash burn is relatively controlled. The company posted a net loss of less than $500,000 in 2020.

Investors should note that Datagran’s 2021 financial performance was dramatically different, however. According to the founder, the company generated just $174,000 in revenue in 2021 — a 90% drop from 2020 revenue. The company’s complete 2021 financials aren’t yet available, but Datagran reports 27% revenue growth between the third and fourth quarters of 2021. Given that low revenue, the 27% growth does not seem impressive. Datagran’s overall performance seems to be on an uptrend, but investors should pay close attention to its financials moving forward.

Datagran has also been successful at fundraising. The company has $4.5 million in existing funding from institutional investors, including Telefonica, Quake Capital, and Beresford Partners. Key angel investors, including C-level executives from Uber and Bain & Company, have also pitched in. 

Lastly, Datagran has built an impressive client roster. More than 3,000 customers trust Datagran for their data analysis and machine learning. That list includes Starbucks, Domino’s, PF Chang’s, and Subway. Datagran doesn’t offer many details on the structure of these relationships or the successes these companies have experienced with the Datagran platform. However, assuming that they remain major clients, Datagran has brought on more prominent enterprise clients than many startups are able to within five years. 

Datagran is a relatively low-risk investment because the company has been around for several years, has generated meaningful revenue, caters to several impressive clients, and is backed by a number of institutional investors. Investors should take note of two small risks. First, Datagran is led by a solo founder, which is a riskier arrangement than multiple co-founders. If anything were to happen to the founder or if he were to leave Datagran, it could jeopardize the company’s success. Second, Datagran is raising a Crowd SAFE rather than an equity round, which decreases some certainty about investor returns. Otherwise, Datagran is a stable, low-risk investment opportunity.

Datagran has a successful track record after several years in business, but the company still faces a few hurdles that investors should consider. First and foremost, it’s a concerning sign that revenue declined by almost $1 million between 2019 and 2020. Some of that dip is likely due to the pandemic, which is understandable. However, the dip is so large that Datagran may have made some sort of pivot or other change which isn’t properly explained in raise materials. It’s also a red flag that Datagran generated just $174,000 in revenue in 2021 — a drastic drop from 2020 revenue. It would be beneficial for investors to examine 2021 financials and determine whether the negative revenue trend seems likely to continue.

In addition, it’s worth noting that Datagran is operating in a nascent industry that has historically been dominated by major players, including Amazon and Microsoft Azure. Large-scale enterprises that already have a robust machine-learning operation probably have little reason to switch to a lighter-weight tool like Datagran. Therefore, Datagran’s success rides on more small and medium-sized businesses investing in machine learning. That trend isn’t quite prevalent in 2022, so Datagran could be a bit too far ahead of its time.

The machine-learning industry is growing rapidly. It’s reasonable to assume that businesses of all shapes and sizes will begin incorporating machine learning into their strategic analysis in coming years. When they do, they’ll need a tool that is a bit more user-friendly than legacy machine-learning platforms, and they’ll likely appreciate the ability to play around with a free self-serve flow. Datagran can provide those key benefits, using a model that mimics how Zapier rapidly created hundreds of thousands of users exploring no-code automation for the first time. 

Plus, Datagran has notched several key successes that provide positive signals of future growth. In just its second year in business, Datagran brought in more than $2.5 million in revenue. The company has secured $4.5 million in venture funding from institutional investors and prominent angel investors alike. Major corporations, including Starbucks and Domino’s, use Datagran. The company has proven its ability to make connections, win revenue-generating users, and sustain a business. This combination of a high-growth industry, differentiated high-tech software platform, and well-executed operational plan signals a potentially lucrative opportunity for investors.

Datagran offers a machine-learning-as-a-service software platform that allows businesses to integrate all of their data sources, visualize that data, and build machine-learning models on top of it. Investors should note that Datagran has had inconsistent revenue over the past couple of years and is competing against large legacy data integration providers in its quest to win market share.

However, Datagran is appealing to a distinctly different target customer than the enterprises who want to contract with Amazon or Microsoft Azure. Datagran is a self-serve platform that is more accessible for smaller data teams. Datagran hopes to emulate Zapier in bringing a technical discipline that seems intimidating (like automation or machine learning) into the mainstream and has already had success in doing so. Datagran’s platform is well positioned within the rapidly expanding machine learning market, which should see more businesses of all shapes and sizes adopt machine learning in coming years. The company has a balanced team, and its current raise is fairly priced for investors. Therefore, Datagran has been rated a Deal to Watch. 

For questions regarding the KingsCrowd analyst report or ratings for this company, please reach out to support@kingscrowd.com. 

Analysis written on March 17, 2022.