This Startup Is Using A.I. to Help People Find the Job of Their Dreams
Contributor, Inc.com@GlennLeibowitz
Matching suitable candidates with the right roles is hard work. This startup is making the whole process easier.
There’s a rising level of anxiety around artificial intelligence and automation, and the potential threat to jobs. Recent estimates say that nearly half of all jobs are automatable using technologies that already exist today.
One startup, however, is using AI not to destroy jobs, but to create new ones. Avrio, a Boston-based startup founded by Nachi Junankar, has developed a platform that uses AI and machine learning to help recruiting agencies and corporate recruiters find suitable candidates for job openings.
Nachi Junankar, Founder and CEO, Avrio
CREDIT: Courtesy Avrio
Their system makes it easier for recruiters to identify qualified candidates from among thousands of job-seekers. And the system allows job-seekers to identify job opportunities that best fit their skill sets, experience, and career aspirations.
While most companies today have systems that take in resumes from job sites and company career sites, and some advertise keyword-based job matching capabilities, Avrio’s AI-based system actually does the work of reviewing and analyzing millions of data points, scores and ranks candidates, and matches them to jobs available in a company. This allows recruiters to focus on doing the work that humans do best, like selling and relationship building.
After two rounds of funding from investors such as NXT Ventures, a Boston-based venture capital firm led by Raymond Chang, they’re about to launch a third round to start scaling up their team from the 14 employees they currently have.
The following are edited excerpts from my conversation with Junankar:
Why did you decide to launch Avrio?
Companies have a wealth of HR and recruitment on candidates they can use for a variety of purposes, predominantly for recruiting and hiring process internally, much of which is sitting unutilized.
We built Avrio for a couple of fundamental purposes. First, to let humans do what they are best at, and let machines do what they’re best at. Humans are good at building relationships and selling, whereas machines are good at analyzing large data sets and doing the cognitive work of matching, scoring, and ranking candidates.
Second, we have to support the job seeker in a significant way, offering them a rich experience, transparency, and valuable insights into their candidacy vis-a-vis a particular set of jobs. Today, applicants live in an opaque world, where they don’t even hear back about their candidacy.
Our platform provides candidates valuable information about their candidacy on a real time basis. We tell them what jobs they are best suited to, so they get a lot of support and hand holding through the process. For example, we provide insight into whether they’ve scored well for a particular job. It could be something as simple as “Hey Joe, we see that you’re applying for job x and you are scoring 55, but here are some other jobs that you are scoring in the 70's.” That’s highly valuable, time-saving information for the candidate.
In general, we’ve believed that having an AI-driven conversation with a candidate is highly valuable to both parties.
How does the platform help recruiters exactly?
Avrio AI is a platform that does away with a lot of low value, repetitive tasks for recruiters. Recruiters spend a lot of hours looking at resumes and jobs . They will tell you that this is not the best use of their time or talent. And because we are human, recruiters may conduct an uneven analysis of the data, not to mention introduce biases into their analysis. Avrio AI sucks in talent and jobs data from the ATS using an API and does all the work needed to match, score, rank and screen candidates.
On the recruiter side, we have an understanding of what the job requirements are, what the “must have” skills are, and all the nuances of a job description. We then analyze data through a set of matching and scoring algorithms using lots of meaningful data points.
So if you apply to job X and you’re not a good fit for that job, that’s okay, we’ll tell both parties. “Joe applied for the marketing manager position, but he’s a better fit for marketing designer jobs.” Once this matching is done, we give the recruiter a list of candidates with the highest scores.
A typical recruiter looks at 20–50 jobs at any given time and probably can’t remember all of the nuances of who is fit for what jobs. The machine says here’s a scorecard for every single candidate. We’ve done all the work for the recruiter.
What about candidates? How does the system work for them?
We also reach out to the candidate. Anyone who scores over a 50, for example, we’ll reach out using text messaging or Slack or Facebook. “Hey Alison, you are matched up for this job at Company Y. We’d love to chat with you, do you have a minute?” When they respond that they want to chat, we then ask them to pick a platform, like text messaging and our robot starts texting them.
We always make it clear that they are talking to an AI. Due to our sophisticated matching, we have an intelligent and highly contextual conversation with the candidate about this job, their skills, preferences and so forth. For instance, we ask them questions like, “Hey, have you led a team before? How big was the team? How long did you lead this team? Why is there a gap in your employment history? Are you allowed to work in this country? Have you done work in machine learning?”
Your system asks questions, but can it answer them?
Yes. Our AI can not only ask a candidate’s questions, it can also answer questions they might ask us like “How do I match up for this job? Are there any other jobs can match up to? How do I stack up to other candidates? How quickly are they looking to hire someone? What’s the culture like? Are there beer Fridays? Do they provide child care?”
This Q&A is entirely automated. Through this conversation a few things happen. First, we update the candidate’s profile and FitScore, which is Avrio’s trademarked algorithm that uses past work experience, education, and certifications to help recruiters evaluate candidates against specific positions on a scale from 0–100.
We will then transcribe this entire conversation and stick it in the notes section. When we finish this conversation, we reach out to the recruiter and ping them, “Hey recruiter, we spoke to Alison. She scored 85. Here’s the transcript. We confirmed these skills, salary expectation, etc.”
The recruiter’s job gets really simple. Now their job is to evangelize with the candidate and the hiring manager.
There’s no reason why in 5–10 years we can’t completely change a recruiter’s job to be much more of a consultative role, rather than having to focus on doing transactional work every day.
(Note: Avrio is not a client of mine, nor do I have any other business dealings with the company.)
The opinions expressed here by Inc.com columnists are their own, not those of Inc.com.
PUBLISHED ON: SEP 19, 2017
