With 4,000 SMEs on its books and $6.7 million under its belt, recruitment startup Vervoe is using AI to build a meritocracy

skill-testing Vervoe

Vervoe co-founder Omer Molad. Source: Duct Tape.

Hiring the right talent is critical to the success of any venture. But how do you know for sure that someone is the best choice when you’re limited to fleeting interviews and bullet-point lists of previous work experience?

Omer Molad and David Weinberg’s solution is Vervoe: an AI-powered skill-testing platform that helps enterprises hire candidates based on verifiable performance, rather than background.

Inspired by Molad’s troubles with finding work, despite knowing he was capable, and difficulties both Molad and his co-founder Weinberg experienced hiring their own staff later on, the pair realised that an impressive CV is not an honest indicator of someone’s skills.

Grades aren’t everything 

“I grew up in Tel Aviv, but also spent part of my childhood in Melbourne. I completed high school in Israel and then spent some time in the military,” Omer Molad told Duct Tape.

“Israel is a massive entrepreneurship and tech hub, and I spent a couple of years working in startups there. I then moved to Melbourne and began applying for tech jobs, but found I couldn’t even get an interview.

“I realised Australian society is quite conservative; I didn’t have a university degree and had a Middle-Eastern sounding name that no one could pronounce. No one valued that I had worked in multiple startups and been an officer in the military. So I enrolled in a law and commerce degree at Melbourne University.

“After I had a degree from a good university, I was more ‘credible’ and got accepted into ANZ’s graduate program. I worked in banking for 10 years, between ANZ and NAB. I also spent two years at the Australian Red Cross doing international emergency response. 

“At NAB, I was in charge of a team of 25 people and was constantly hiring and reshaping the team.

“But I noticed that many people with fancy résumés couldn’t actually apply their skills in different environments in the way we needed.

“The actual stars of the team weren’t from the top universities, didn’t necessarily have the best grades, or come from a big-logo company. But they were curious, hardworking and creative.

“So it became obvious that there’s a massive disconnect between the way people were telegraphing their skills and what they were actually capable of performing.”

Reality-based skill testing 

“This brought me back to my own experience as a candidate arriving in Melbourne. I couldn’t put forward what I could contribute — I couldn’t even get in the door.

“I spoke with my friend, and now co-founder, David who had previously worked in Silicon Valley, and he had found the same thing — that you couldn’t differentiate between the skills of the people who had gone to Stanford or were self-taught.

“We had both read an article about Matt Mullenweg, founder of WordPress — he used to hire people through auditions where he would bring people in to work for the company for one week.

“We loved this concept and began exploring how we could recreate the same experience of watching people work in a real environment.

“But bringing people in for a week is not very scalable, so we wondered how we could get 200 candidates to do 20 minutes of work online, and use technology to make the experience fun and interpret the data at the same time. We became obsessed with this idea and couldn’t think of anything else until we started working on it. That was the vision for Vervoe.

“We now design scenarios for skill-testing by putting candidates in the situations they will actually face in the job. I often say if you wanted to know how good Roger Federer was at tennis, you wouldn’t have a coffee and chat with him, you’d ask him to hit a ball.

“So we get applicants for a product design role to actually design something, financial analysts to do something in Excel, sales representatives to write a cold email, or edit a sales deck.

“We use machine learning models that automatically grade and rank candidate responses, so we can assess 20 or 20,000 candidates immediately.

“Based on hundreds of data points derived from how candidates perform tasks and interact with our platform, we can predict scores to a really high degree of accuracy.

“Often people are excluded from job applications for not having a university degree, but self-taught people or those with other life experience might perform just as well.

“We also know that people from more fortunate backgrounds often stand out compared to less privileged or underrepresented groups. We de-identify the results so recruiters and hiring managers are less influenced by other factors like name, education or prior work experience.

“We really want to level the playing field by making the choice simply about how well you can do the job and contribute to the organisation. 

“Today we have 4,000 small business and 50 enterprise customers, a team of 23 people distributed across the USA, Europe and Australia, and have raised US$4.5 million ($6.7 million).” 

Leadership through allocation 

“I see my job as founder and CEO as being about allocating capital. Not in the narrow sense of what to spend money on, but how to use the resources that we currently have to achieve a common organisational goal.

“This involves answering a series of questions, such as how to get the best out of people, how to get people to focus on different things, where should we invest as a company?

“It’s confronting as you’re constantly making decisions, most of which are probably going to be wrong, but I really enjoy working with different people and trying to help them get the best out of themselves and do the best work of their lives.

“Sometimes I have to make hard calls regarding people who are not working out, but ultimately I have to get the whole group to create something from scratch and work towards a common goal that we all believe in so deeply. I love that every single day.”

This article was first published in Duct Tape, a publication by Startup Victoria and Victoria University, and has been republished with permission.

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