eqtble, a data analytics platform designed to create what they’re calling a “healthier workplace,” has announced that it has raised $2.7 million in its initial seed funding round.

TechCrunch says that the company — which was founded by Joseph Ifiegbu, the former human resources technology head at Snap who also has a bit of history at WeWork — raised its $2.7 million with help from Initialized Capital, who led the funding round. The funding was also completed with participation from SB Opportunity Fund, RS Ventures and other venture capital firms and angel investors.

The seed funding will reportedly be used to grow eqtble’s engineering team and its platform’s machine learning and visualization capabilities, and user acquisition.

eqtble solves the problem of what’s known as “data fragmentation” amongst companies. When a new employee joins a company, his or her data is usually found in all different parts of the computer system at the company. As a result, companies can often miss important data and correlations — especially if they have a large turnover rate.

But with eqtble, data is collected from more than 100 sources (including Workday, ADP, Oracle, PeopleSoft, Qualtrics, and Culture Amp), and the program delivers insights and visualizations about four main areas: talent recruitment, workforce, engagement (including attrition, or when workers quit) and compensation.

One of the company’s clients used the software to see why so many good potential employees were turning down job offers. As it turned out, their long interview process is what drove most of the potential new hires away.

“If you as an organization are saying ‘we’re going to have six rounds of interviews, it’s going to take three months to interview,’ you’re going to lose out on good candidates,” says Ifiegbu. “Other people are closing candidates within one to two weeks.”

The data generated from eqtble can also be used by companies to aid with their diversity, equity, and inclusion hires — especially if they’re more conscious about it than in previous years’ past.