MOSTLY AI raises $25 million to further commercialize synthetic data in Europe and the US – TechCrunch

Austrian synthetic data company MOSTLY AI announced today that it has raised $25 million from its Series B round. Britain’s Molten Ventures, led the operation, with the participation of new investor Citi Ventures. Two current investors have also returned: Munich-based 42CAP, and Berlin-based Airliebird, which led most of the $5 million Series A first round for AI in 2020.

Synthetic data is fake data, but it is not random: AI mostly uses AI to achieve a high degree of accuracy in its clients’ databases. The company says its data sets “look as real as the company’s original customer data with the same amount of detail, but without the original personal data points”.

Speaking to TechCrunch, MOSTLY AI CEO Tobias Hahn said the company plans to use the proceeds to push the boundaries of what its product can do, grow its team, and gain more clients both in Europe and the US, where it already has offices in New York City.

MOSTLY AI was founded in Vienna in 2017, and the General Data Protection Regulation (GDPR) was implemented across the European Union one year later. This demand for privacy-preserving solutions and the attendant rise of machine learning has created a huge momentum for synthetic data. Gartner predicts that by 2024, 60% of the data used in developing AI and analytics projects will be generated industrially.

Most of the typical customers of AI are banks and Fortune 100 insurance companies, as well as telecom companies. These three highly regulated sectors drive most of the demand for synthetic tabular data, along with healthcare.

Unlike some of its competitors, most AI systems have not focused on healthcare in the past, but it could change. “It’s definitely something we’re watching closely and we’re actually starting some pilot projects this year,” the CEO said.

The democratization of AI means synthetic data will eventually be used far beyond Fortune 100 companies, Han told TechCrunch. So his company plans to serve small organizations and a wide variety of sectors in the future. But until now, it has made sense for most AI to focus on customers at the enterprise level.

It’s enterprise companies right now that have the budgets, need, and sophistication to work with synthetic data, Han said. To match their expectations, most AIs have obtained ISO certifications.

Speaking to Hann, one thing is clear: While the startup has a solid technology foundation, it invests equally in commercializing its technology and in the business value it can add to its customers. “Most AI is driving this emerging and rapidly growing space in terms of customer deployments and expertise,” said Christoph Hornung, chief investment officer at Molten Ventures.

The need to comply with privacy laws such as the GDPR and Consumer Privacy Protection Act (CCPA) is clearly driving the demand for synthetic data, but it is not the only influencing factor. For example, the demand in Europe is also driven by a broader cultural context; While in the United States, he also results from a desire to innovate. For example, use cases can include advanced analytics, predictive algorithms, fraud detection, and pricing models – but without data that can be traced back to specific users.

“Many companies are proactively approaching the space because they realize that customers value privacy,” Han said. “These companies know that they can also gain a competitive advantage when dealing with data and working with it in a way that preserves privacy.”

Seeing more US companies wanting to adopt synthetic data in innovative ways is the main reason most AI want to grow their team in the US, but they are also recruiting generally, both in Vienna and remotely. Its plan is to increase its staff from 35 to 65 people by the end of the year.

Hahn predicts 2022 will be “the year that synthetic data will take off,” and beyond this year, “a really strong decade for synthetic data.” This will be supported by the growing demand for responsible AI, centered around key concepts such as AI fairness and explainability. Synthetic data helps answer these challenges. “It enables companies to augment their data sets and de-bias,” Han said.

Aside from machine learning, most AI sees a lot of potential in using synthetic data in software testing. Supporting these use cases requires that synthetic data not only be accessible to data scientists, but also software engineers and quality testers. Bearing in mind that MOSTLY AI appeared a few months ago with version 2.0 of its platform. “Most AI 2.0 can be implemented on-premises or in a private cloud, and adapts to the different data structures of the company that uses it,” the company wrote at the time.

“We are clearly a B2B software infrastructure company,” Han said. In its A and B rounds, the company looked for investors who understood this approach.

Hahn emphasized when I asked that Molten Ventures is publicly listed and therefore not subject to typical financing cycles, it does hold some significance. “Having this long-term commitment from a partner is something that has been very attractive to us, because it’s a little bit more flexible.”

It also doesn’t hurt that Citi Ventures is the investment arm of Citigroup, and that it’s headquartered in the US “We’re growing the team significantly in the US, and it’s always great to have a US-based investor who can,” Hahn said.

With $25 million in new funding and an increased US presence, most AI will now have more resources to compete with other companies in their sector of the synthetic data space. These include Tonic.ai, which raised $35 million in Series B last September; Gretel AI, which revealed a $50 million Series B round last October; and UK-funded startup Hazy from the start, as well as players focused on specific sectors.

“We’re seeing more and more players emerging in the space and in the market in general, so it definitely shows there’s a lot of interest out there,” Han said.

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