This Start-up Founder Wants to Eliminate the ‘Black Hole’
Eyal Grayevsky has firsthand experience of the “black hole” many job candidates complain about—applying for a job or sitting down for an interview and then hearing nothing back from the employer.
Unlike most candidates, however, Grayevsky was in a position do something about it. The company he founded three years ago, Mya Systems, makes a product designed to help spare candidates from the dreaded black hole while making it easier for companies to find and communicate with talent.
Grayevsky himself wasn’t new to the talent-acquisition business: his father founded a staffing firm more than three decades ago, and Grayevsky worked there as a technical recruiter prior to graduating from college. Having witnessed firsthand the frustrations that can plague jobseekers and recruiters alike, his plan is for Mya Systems to carve out a niche for itself by using AI to make those headaches go away.
Mya Systems is one of a number of recruit-tech vendors that are using natural-language processing to help make the talent-acquisition process easier and more effective for candidates and recruiters alike. Its flagship product, Mya, is an “AI recruiting assistant” that uses NLP for candidate outreach, helping them identify positions they may be ideally suited for. The tool also has the capability to automatically schedule interviews and help recruiters narrow down the list of qualified candidates from large pools of applicants.
The company has grown rapidly since its 2016 founding and currently counts 120 large companies as its clients, including L’Oreal, Adecco Group and RPO firm Sevenstep. It now has offices in London and Munich, in addition to its headquarters in San Francisco.
I recently spoke with Grayevsky about his firm and his plans for its future.
Tell us a bit about your own background and why you decided to start Mya Systems.
I’ve been pretty involved with my dad’s staffing company since I was a kid. My own experience as a job candidate began after I graduated college with a degree in finance and was searching for jobs in San Francisco. It was really frustrating—I applied for a bunch of jobs in sales and finance and rarely heard back from the companies. At that point I decided to start my own company, an online jobs marketplace called FirstJob. My cofounder and I worked with companies that did high-volume hiring and learned a ton about the pitfalls of the marketplace experience and the inefficiencies of the recruiting process. We used the insights we gained to launch Mya Systems three years ago. The initial inspiration behind Mya was figuring how to eliminate that black-hole experience where 80 percent of candidates never hear back from companies. Since then we’ve built the solution into a robust conversational AI platform, and now we’re applying this to multiple phases of the recruiting experience.
How do you ensure candidates are comfortable with this process?
Candidates know they’re interacting with a chatbot. Usually, they wait weeks to hear back from an employer, if they hear back at all. But, having this opportunity to instantly engage with and having a forum in which to express their value to an employer is a huge step up from the experience that existed before. We’ve seen candidates react really positively to this. I think what sets our approach apart from others is that we’ve invested heavily in the development of conversational AI. Mya truly understands what you’re saying and uses that to guide you, as a candidate, through a seamless experience.
How does this typically play out in an actual conversation?
For example, if we’re engaging in screening conversations for retail-sales jobs, we’re able to build a conversation that caters to the specific dialogue for candidates applying for retail sales. The types of questions we ask are scaled across a really large volume of candidates and, thus, benefit from all those learnings. For example, if we have a conversation about shift availability and we ask the same question to 10,000 candidates, now we have access to all this high-quality data around how all the different variations of responses enable the system to learn. So over time, we’re able to build out and improve the underlying AI through experience. The type of questions candidates ask can be used to support and understand queries about days of the week they’re available, the times during the days they’re available, and so on.
What sort of companies tend to be most interested in your solution?
We typically gravitate to areas where clients have high-volume needs, on the hourly and the professional side. We’ve had a lot of success in the retail category, along with hourly positions at call centers, warehouses, hospitality and food services. Over time, we’ve expanded to professional-level jobs as well in areas like healthcare, IT and engineering. We’re constantly adding more in terms of our conversational abilities across job domains.