KC-tested GoGetter uses AI to bring back human interaction in hiring talent (minus the middleman)

As a software contractor at Cerner for two years, Naga Rayapati saw more than 40 percent of his paycheck go into the pockets of middlemen, he said.

“While the contractor puts in their heart and soul working for the company, these ‘preferred vendors’ reap the benefits,” said Rayapati, referring to third parties in the hiring chain that often brokered his contract jobs.

His solution — the recently launched GoGetter, an online job matching marketplace for software engineers — uses artificial intelligence and machine learning to remove the middlemen from the hiring process and bring contractors and hiring managers onto the same platform, he said. 

Rise of the gig economy 

With the gig economy continuing its explosion, the demand for a contingent workforce has skyrocketed over the years, said Jennifer Brown, technology consultant at GoGetter.

Naga Rayapati, GoGetter

“Gig economy workers actually have higher employee engagement numbers than full-time workers,” Brown said. “Contractors can come in and fill in the gaps on projects and pick up projects that have a sense of urgency.”

But contractors can have a hard time connecting directly to their potential employer, said Rayapati, now a Silicon Valley AI entrepreneur. From turning in their job applications to being placed in new jobs, the hiring process through third-party entities is riddled with difficulties, he said.

“I realized that the process is so inefficient and highly opaque because if the hiring manager wanted to hire the contractor to a full-time employee, they won’t know which companies are associated in the process,” Rayapati said about his initial research on the process. 

Solving a ‘chicken and egg’ problem 

Since its creation in 2016, GoGetter has on-boarded 20,000 software contractors on its platform to supply talent to firms looking to hire, Rayapati said. 

Once a contractor is hired, GoGetter receives 20 percent of the contractor’s salary which, the founder said, is less than how much other third party entities charge. 

“It’s a different ball game altogether for us,” he said. “We have to solve the chicken and egg problem on both the supply side and on the demand side.” 

The angel investor-backed startup has raised about half a million dollars since it tested its product first in Rolla, Missouri, and then in Kansas City, Rayapati said. The firm hoped to access the talent originating in Kansas City, as well as recent graduates from the Missouri University of Science and Technology. 

“The IT industry in Kansas City is like a chess match,” Brown said. “The supply and demand of talent is way off, and it’s about moving people from place to place skillfully.” 

Diversifying the data 

GoGetter uses artificial intelligence to read data from a contractor’s résumé and fill out his or her’s profiles, Rayapati explained. With “collaborative filtering,” algorithms make suggestions of prospective companies based on the contractor’s previous experiences and preferences. 

“Our platform also uses a diversity index and face recognition to show contractors how diverse a company’s board of directors are, and we’ve also used machine learning to predict hourly wages to contractors,” Rayapati said. 

Algorithms are not free of bugs and biases, he said, citing infamous examples like when faulty algorithms used by a previous version of Google Photos classified people of color as gorillas. 

“This is one of the biggest problems with AI algorithms,” Rayapati said. “You need to make sure your data is as diversified as possible. We recruit a diverse team of engineers to minimize bias in our algorithms.” 

The success of their diversified data sets have created facial recognition technology that is able to detect non-traditional genders as well, Rayapati said. Their algorithms are producing better and more accurate results than some of the firms already in place, he said.

This resulted in the making of a spin-off called Guise.ai that integrates face recognition capabilities with their prospective client’s existing products, he said. 

“We are seeing significantly serious breakthroughs with respect to gender recognition, ethnicity recognition, face detection, and celebrity recognition,” he said, citing the use of the technology for marketing firms, their main clients.

Shortage of talent acquisition professionals means that it’s harder for companies to recruit directly, Brown said. 

“The future of staffing is technology and soft skills together,” she said “AI is meant to make people more efficient, and bring it back to human interaction.”

This story was produced through a collaboration between Missouri Business Alert and Startland News.