Tonic.ai raises $35M Series B to help engineers create synthetic data sets

·3-min read
A close-up on a data set of random binary numbers

When engineers are building software, they often run into issues around testing it without using actual customer data. Creating a meaningful test set can be time-consuming and challenging. Tonic.ai, a startup that helps engineers create synthetic data sets, is trying to fix that, and today the company announced a $35 million Series B.

Insight Partners led the round with participation from GGV Capital, Bloomberg Beta, William Smith from Octave, Heavybit and Silicon Valley CISO Investments. The company has now raised a total of $45 million, according to Crunchbase data.

Company CEO and co-founder Ian Coe says the goal of the company is to provide production-like data for developers that keeps governance and compliance folks inside an organization happy. "Tonic is a data transformation company that leverages synthetic data, differential privacy and distributed computing. We de-identify sensitive data, while preserving all the value of that data so that developers can use it for building and testing software," Coe explained to me.

What they do is create these "fake" data sets from the actual data, so that it is very much like the information sitting in the database. But the solution involves more than simply anonymizing some names to comply with legal and ethical standards. It often involves extremely complex connections that move across data repositories and complex databases.

He says that's why it's not something someone can easily mimic or do themselves. There is a lot going on under the hood to make this happen. As one example, making sure that if you change a name in one place, it changes it consistently across every point in the application production process where that name might occur without any leakage of actual data.

For now at least, they are going to concentrate on developers as primary target customers, even though the product could have utility for other roles like data scientists. The company launched in 2019 and while they see other startups like Gretel and Synthetaic trying to solve parts of this problem, Coe says that he hasn't seen competitive solutions that really attack the complex range of the enterprise set of issues.

"We see some other startups that are sort of contemporaries with us, and generally what we see is that they're not really solving the enterprise data side of the problem, a lot of that really annoying data infrastructure work and really making it possible to integrate with the CI/CD pipeline, and I do see that as a big differentiator for Tonic," he said.

The company has around 40 employees at the moment. As they make a push to hire more people with this new influx of capital, they hope to reach at least a 100 in 2022. To help make that happen, they recently hired a new head of people and talent, and it's part of her job to ensure that the company is building a diverse employee base.

"Our head of talent is doing some special recruiting initiatives this year to reach out [to historically underrepresented groups] and we're using some different services that I know specialize in diverse recruiting," he said.

Our goal is to create a safe and engaging place for users to connect over interests and passions. In order to improve our community experience, we are temporarily suspending article commenting