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Posted by Richy George on 27 May, 2020This post was originally published on this site
Toro’s founders started at Uber helping monitor the data quality in the company’s vast data catalogs, and they wanted to put that experience to work for a more general audience. Today, the company announced a $4 million seed round.
The round was co-led by Costanoa Ventures and Point72 Ventures with help from a number of individual investors.
Company co-founder and CEO Kyle Kirwin says the startup wanted to bring the kind of automated monitoring we have in applications performance monitoring products to data. Instead of getting an alert when the application is performing poorly, you would get an alert that there is an issue with the data.
“We’re building a monitoring platform that helps data teams find problems in their data content before that gets into dashboards and machine learning models and other places where problems in the data could cause a lot of damage,” Kirwin told TechCrunch.
When it comes to data, there are specific kinds of issues a product like Toro would be looking at. It might be a figure that falls outside of a specific dollar range that could be indicative of fraud, or it could be simply a mistake in how the data was labeled that is different from previous ways that could break a model.
The founders learned the lessons they use to build Toro while working on the data team at Uber. They had helped build tools there to find these kinds of problems, but in a way that was highly specific to Uber. When they started Toro, they needed to build a more general purpose tool.
The product works by understanding what it’s looking at in terms of data, and what the normal thresholds are for a particular type of data. Anything that falls outside of the threshold for a particular data point would trigger an alert, and the data team would need to go to work to fix the problem.
Casey Aylward, vice president at Costanoa Ventures likes the pedigree of this team and the problem it’s trying to solve. “Despite its importance, data quality has remained a challenge for many enterprise companies,” he said in a statement. He added, “[The co-founders] deep experience building several of Uber’s internal data tools makes them uniquely qualified to build the best solution.”
The company has been at this for just over a year and have been keeping it lean with 4 employees including the two co-founders, but they do have plans to add a couple of data scientists in the coming year as they continue to build out the product.
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