Stop Rejecting Talent with Ritu Mohanka
Amsterdam Edition: Talent, Bot Wars & The Death of the Click
Live from Amsterdam at the House of HR, Chad Sowash sits down with VONQ CEO Ritu Mohanka to diagnose recruitment’s newest self-inflicted disaster: candidate AI spam.
While job seekers unleash bots that mass-blast 10,000 applications while they sleep, employers are still paying agencies by the click for mountains of unusable garbage. Ritu explains why VONQ blew up the old distribution model to build an AI agentic screener—one meant to filter people in rather than toss qualified candidates straight into the digital trash can.
What’s on deck in this episode:
The Perverse Incentive of Pay-Per-Click
Knockout Questions Are Garbage
Europe’s Bureaucracy vs. America's Chaos
Why Big Tech Doesn’t Get Hiring
Giving 30% of Your Life Back
Enjoy!
PODCAST TRANSCRIPTION
Chad Sowash: Welcome to the Amsterdam Talks. I'm here today with Ritu Mohanka. She's the CEO of a little company called VONQ. You're in London, but VONQ, you have headquarters in Amsterdam?
Ritu Mohanka: Rotterdam.
Chad Sowash: And Rotterdam, okay, so close.
Ritu Mohanka: Close.
Chad Sowash: Rotterdam. So we're in beautiful Amsterdam today getting ready for the House of HR show, so there's going to be some clanging in the background, but it's all fun, kids. So, Ritu, tell us a little bit about yourself.
Ritu Mohanka: Well, first and foremost, thank you for having me, Chad.
Chad Sowash: You're welcome.
Ritu Mohanka: Tell me about myself: I am a mother of two boys, 17 and 15.
Chad Sowash: Oh. Okay.
Ritu Mohanka: That keeps me truly humble and grounded. I have been in the HR tech space for over two decades. I'm still young. I joined VONQ two and a half years ago, and today we turned 20 years young as a company.
Chad Sowash: Yeah.
Ritu Mohanka: I am still based in London, and that was a choice I made, but I commute to Rotterdam every week.
Chad Sowash: Okay. VONQ has really metamorphosized, I guess you can say, in the past year or so. Now, I know there's been a lot happening behind the scenes, and you've been there for a couple of years, right? So we're going to say this is all your fault. So talk a little bit about that. VONQ was really known as a distribution system, and today that's just a little piece of it, right? So can you talk a little bit about that from a vision standpoint? And again, this is really—Bill Fisher was here before LLMs were big, hot, and fast, but you guys were on this road much earlier. Talk a little bit about that.
Ritu Mohanka: Absolutely, Chad. So, as you said, VONQ has a huge history both from expertise and experience perspective.
Chad Sowash: Yeah.
Ritu Mohanka: When I joined VONQ, we had all the fabulous ingredients a good company should have. That is: great technology, great people, really deep relationships with customers, and more importantly, great relationships with ATSs and HCM platforms.
Chad Sowash: Yeah.
Ritu Mohanka: What we had to ask at that time to ourselves is: are we still optimizing for distribution, or are we optimizing for the outcome that our customers are looking for? Which is not "Can I get 400 applications today?", but rather, "Can I get the right ones applying for the role today?"
Chad Sowash: Yeah, yeah.
Ritu Mohanka: And I think that was a shift we had to ask ourselves, because the industry was changing so fast, and it was an extraordinary moment for me to come in and say, "Well, this is our opportunity to change as well."
Chad Sowash: I mean, that's hard, though, because to be quite frank, a lot of those agencies that are out there, a lot of those boards that are out there, they optimize just to get clicks because that's how they get revenue.
Ritu Mohanka: Yes.
Chad Sowash: It's not about—and you hear about, "We're going to drive quality," but quality means less clicks. Quality means less money for that organization. So it's been very hard for decades to be able to believe that that's been the case, right? That you're actually driving me quality. How are you guys doing that differently, right? When you're talking to a customer and they're like, "Okay, Ritu, we've heard this before," how do you talk to them? How do you articulate that, "Yeah, totally get that, but..."?
Ritu Mohanka: Let me give you some context first, Chad. I'm going to start with candidates, because our industry has spent far too much time talking about what recruiters will do with AI.
Chad Sowash: Yeah.
Ritu Mohanka: But candidates haven't been sitting still. They have found AI themselves. And as they find AI, they started asking the question, "Can you help me write a great CV?"
Chad Sowash: Yeah.
Ritu Mohanka: Then they said, "Okay, can you help me tailor this job application for this particular role?" Then they said, "Go find me the right, relevant roles for me."
Chad Sowash: Right.
Ritu Mohanka: And then they said, "Hey, agent, act on my behalf and go not only find a job, but apply for it. Help me even coordinate next steps and compare different opportunities. And by the way, I'm giving you permission to completely act and stay sort of be active in my behalf."
Chad Sowash: So the problem's worse today than it ever has been.
Ritu Mohanka: Absolutely.
Chad Sowash: Okay.
Ritu Mohanka: So given that candidates have found AI not just as a tool, but rather an agent that acts on their behalf—
Chad Sowash: Yeah.
Ritu Mohanka: Employers on the other hand said, "Well, we've got to meet the other side, too." So whilst AI applications creates volume, it also creates the most perfectly polished CVs and resumes and cover letters.
Chad Sowash: They all look the same.
Ritu Mohanka: Exactly. So what happens? That traditional signals employers used to have where they could compare two candidates and tell the difference, they can't do that anymore.
Chad Sowash: Yeah.
Ritu Mohanka: So it isn't really more about how many clicks you get or cost-per-application, but it has really become about: can I, employer A, B, and C, give you the relevant candidates who are high intent without spending only on advertising and clicks, but rather screened, vetted, scored candidates? And I think that's the journey we went on, asking our customers to say, "What is it that really your problem you're solving for?" And the problem they were solving for is not that we want to pay all this money for advertising—they will still advertise—however, we want to pay for advertising on outcome basis. Give us the outcome, not just spend on clicks and how many applications we get. And I think that's the shift we made last year when we launched our cost-per-application-click model.
Chad Sowash: Well, and I think—I mean, that's really cost-per-qualified application, right? So I mean, that's even another level. You've got the cost-per-application—an application's an application—but if it's a qualified application, something entirely different. And what you guys are doing is you're doing that screening upfront to be able to say, "Do you meet the requirements?" And tell me what you think about this: I've always thought that we try to overengineer everything. We're humans, we overengineer everything. And we've overengineered the process, and really all we need to know is, do you meet the requirements?
Ritu Mohanka: Totally.
Chad Sowash: And if you do at that point, when we're talking about making more money as a company, it just makes sense. If I deliver you a click, what's worth more: a click, an application (doesn't mean it's qualified), or a qualified individual?
Ritu Mohanka: Indeed, a qualified individual. And again, as you said, Chad, we've made everything so complicated. Even when we talk about qualified, people get so hung up in what is qualified. It's very simple, right? It's really, really simple.
Chad Sowash: Well, they talk quality. Quality means nothing, right? Qualified means something, yeah.
Ritu Mohanka: Exactly. Exactly. Relevant, high-intent. You really did mean to apply for this job. Your agent wasn't acting on your behalf and applying to 10,000 jobs at the same time. And that's exactly what a relevant, high-intent candidate is. It's about vetting those candidates for: Can you drive, if that job requires that? Do you have a license to practice something? Can you work Saturdays? Those are the kind of things that helps me say, "Okay, I've weeded out the noise, and I've given you real signals to say this candidate is a relevant, high-intent, qualified candidate." And I think it's as simple as that.
Chad Sowash: Yeah. Well, and it also gets away from the hiring manager's "want-to-haves," right? And I know this is something that staffing has always had problems with over the years is like, look, you're paying for what you must have, what you needed, what's required for the job. Now, as we've talked about overengineering systems, talk to me about how you guys have really focused on going the other way and going to more of a simplified process.
Ritu Mohanka: Well, the question is very simple: what is the outcome the customer wants to drive? What are the problems you're trying to solve? And even if you have a great consumer brand, perhaps you don't have a great employer brand. Or perhaps you have a great employer brand for certain roles, but not for other roles. So let's focus our energy on those other roles that perhaps you're not known for. You imagine, if you think about a bank, a few years ago no one would have imagined it's a technology company.
Chad Sowash: Oh, yeah.
Ritu Mohanka: But now all banks consider themselves to be technology companies. For that, they require a huge number of people who are well versed in technology, or programmers, or software engineers. So they have to elevate their brand to ensure that those individuals don't just go work for Google and Microsoft, they also apply to banks such as—let's assume the German bank we work with.
Chad Sowash: Yeah.
Ritu Mohanka: What that means is we help those organizations to say, "Okay, what do you want your people to know you as?" So really elevating your brand first. But we don't do that, again, as an agency model of saying, "Hey, let's charge you €100,000, and by the way, we'll give you some content six months later, and by the way, you may not even like it." What we've done is we've used agentic platform to say, "Let's help you generate content on-brand with a human in the loop, the right safeguarding that you need to have, but be able to generate content on the fly so you can really go reach out to those passive candidates who are perhaps thinking of applying to Google or Microsoft, but not to your organization." That's the first problem we're solving.
Ritu Mohanka: So it's not just about distribution for the sake of distribution. It's about elevating your brand when it truly matters, with content that's relevant, on-brand, but really quick. The agility really matters.
Ritu Mohanka: Then it's about saying, "Well, now I have all these applications, how do I simplify that?" Well, don't spend human time here. I genuinely believe if someone says to me, "So you're telling me all these tasks are being automated by AI?" Absolutely, yes, why not? Because if you can take those tasks that don't require human intervention, then you're elevating the role of a human or a recruiter. So let's get screening right at the top of the funnel, at the point of application, for a candidate to simply say that they have what they require to be able to apply for that job.
Chad Sowash: Yeah.
Ritu Mohanka: So when that candidate then goes to an ATS, it is a highly relevant candidate, but also both the recruiter has a great experience and the candidate has a great experience. They haven't been waiting around for weeks or filling up a form that takes 90 minutes to fill and there are 90 fields to complete, and then they drop out eventually.
Chad Sowash: Well, and they won't do that anyway. They'll have their agent fill it out. Exactly, exactly.
Ritu Mohanka: Exactly.
Chad Sowash: We were just talking to Kobe here from Heineken, who leads talent Heineken in Amsterdam and Belgium. And he said that 30% of his recruiters' time is taken doing interview scheduling, which everybody hates, right?
Ritu Mohanka: Absolutely.
Chad Sowash: So I mean, there are so many different opportunities, I think as you had said, to be able to really give the human 30% of their time back to be able to engage with other humans, and then also allow agents to be able to literally screen through to ensure that you're getting qualified candidates at that point. Now, you said something earlier that I want you to elaborate on. You were talking about being able to create the content upfront. Is there an agent doing that? How is that actually working? How is that being received from companies? Talk a little bit more about that.
Ritu Mohanka: Well, you mentioned Heineken, so Heineken was our design partner.
Chad Sowash: Okay.
Ritu Mohanka: They gave us the inspiration of going really fast.
Chad Sowash: That's a nice flex, right?
Ritu Mohanka: Yes, indeed. And again, it was simply Heineken came to us: "We need to find X number of account managers for this specific city. Help us get there. Female account managers."
Chad Sowash: Yes.
Ritu Mohanka: And again, as you can imagine, Heineken brand and female account managers in a certain location poses its own challenges. It took a long time to get their agency to generate a bunch of videos or content. It took far too long, and when they got the results, they weren't even that happy. So they came to us and said, "We have no time. We need to hire X number of people in this role very quickly. Help us get there." And that's when our genius, brilliant CTO said, "Why don't we build this?" And there we go.
Ritu Mohanka: Our agentic flow starts from: How do we help organizations write a really good job description? How do we optimize to the right channels we should distribute? How do we attract? And in terms of attract, how do we create social content so we can attract those candidates, to how do we screen, interview, and score? And that's the agentic flow where human intervention is there—there is human in the loop—but essentially it's a full agentic flow that allows an organization to very quickly go from "I have a challenge" to "Here's the outcome I want to drive."
Chad Sowash: Right. For years, we've been sold a bill of goods. And I mean, there's always been great companies, there's always been ones that are kind of like selling you vaporware. What's been the reception? Because it's like, "Ritu, this just sounds too good to be true." You obviously have big-name design partners. What has been the reception, and how many different clients are actually using different aspects of Echo?
Ritu Mohanka: The reception has been really good, and the reason for that, Chad, is we didn't build it in our labs in isolation. Even when we started, so even when I joined VONQ, Bill had already built a lot of that technology, which no one even were talking about it at that time.
Chad Sowash: Mhm.
Ritu Mohanka: So it was really about how do we take this technology and go to market, but with our customers? So we asked the likes of Adecco, SoftwareOne, a German bank, saying, "Will you be our design partners? This will be a proof of concept for X number of months. There's got to be feedback loops on a weekly basis. We've got to have recruiters involved." So this isn't about someone sitting in the ivory tower and saying, "Let's use VONQ." This is really: can we truly, genuinely elevate the role of recruiters and involve them where human value matters, and where it doesn't, can we take away those tasks away from them?
Ritu Mohanka: So it was a very iterative process of almost nine months before we launched it out into the public, with work constantly happening and saying, "What are we learning? How do we change things?"
Ritu Mohanka: Simple things like we were doing a different type of a scoring, and Adecco came to us and said, "Well, you give us 70 as a score, immediately people think it's 70 out of 100, so it's 70%, that's not good enough, I want 90%." That is a simple example. So we're like, "Okay, well, that makes sense." So we changed our scoring to out of 250 points for each candidate across 15 vectors based completely on the job description. So it was a lot of learning, it was a lot of iterating, it was a lot of experiment, it was a lot of failing, to which point we said, "Okay, we have enough proof points, enough outcomes to say this is going to be well received in Europe." Because Europe is slightly special, as we all know.
Chad Sowash: Yes. Well, and the special part of it is the EU AI Act, right? So talk a little bit about that, because in the US it's a wild, wild west right now, right? You can pretty much do just about whatever you want. They're dismantling a lot of protections, there's just a lot of things not happening there, right? But in the EU, that's entirely different. So talk a little bit about that. What kind of hoops are you guys going through to be able to ensure that you are complying with—not just complying, but also building for the future?
Ritu Mohanka: And doing the right thing by the people. That's the most important thing. You know, I grew up—I'm digressing, I'll come back to the question. So if you think about what we did was, one, we got lucky. So when Bill built the technology, he designed on the basis of the EU AI Act on the horizon. That was the first thing. Second, when we were testing with our partners, imagine a German bank. It doesn't get more stringent: a German company and a financial services organization. A software technology company have its own challenges, headquartered in Switzerland. And then Adecco has its own challenges. That helped us really think through what are the types of things that's really critical for us to be explainable, to auditable, to be transparent.
Ritu Mohanka: And I think it became very clear that whatever we say is not good enough anymore, because everyone's saying the same thing. So we went out there and said we need to do an external audit of our systems, our practices, and are we truly bias-free? And this audit is not a one-time audit, this is a continuous audit month-over-month to say, are we still adhering to the EU AI Act in terms of transparency, explainability, and auditability? And I think that was critical for us, that we've got to be bias-free.
Ritu Mohanka: And everyone says, "Oh, AI dehumanizes recruitment." It's quite the—
Chad Sowash: It shouldn't.
Ritu Mohanka: It's quite the contrary. If you do it right, if you do it right by the candidates, if you're transparent upfront to the candidate that we are going to use AI to screen, score, and assess you, and then explain to them how AI will be used, but it will not be used for judgment, then you're okay. Candidates actually want to do that, because they don't want to wait around for days and days to get a callback from someone who perhaps doesn't have the time to call that candidate back.
Ritu Mohanka: So I think all those things were fundamental for us to get right upfront even before we launched, so that we had actually candidates write on LinkedIn, "I've just been through the VONQ's AI screening, and what an experience it was, how transparent it was. It was actually fun. It felt quite human." Of course, the voice will always remain slightly robotic, but that's also purposeful, because if it's going to sound completely human, then you might mislead someone thinking it's not an agent asking me questions, it's a human asking me questions.
Chad Sowash: Well, and if you take a look at a lot of the voice tech that's out there today, I mean, even the Notebook LLM, it is fairly seamless. And it is very good. It could be seen as human, and you don't want to come off that way. You want to be transparent. And I mean, for the organizations in the US, another word that you should probably start using is "defensible," because there's so much litigation that's happening in the US because there's not enough legislation. So if you lean too far one way on the legislative side, obviously you do have guardrails, but if you don't, the litigation piece, right?
Ritu Mohanka: Completely. And, Chad, that's what I mean about recruiter confidence. It's about defensibility. Can I defend those scores and why the agent gave this candidate so many scores, this score? If I can't defend that, if I can't explain it, how is a hiring manager or candidate going to believe that? So it is absolutely about recruiter confidence, and that comes from defensibility.
Chad Sowash: Now, can the candidate actually see their score?
Ritu Mohanka: They can't actually see their scores, but as they go along the journey from a chat to a voice, they can actually see that the passing continuously happens not just on their CV, but on the information they share, that we are closing the gap. We are screening them in, we're not screening them out, so they can see, "Okay, I've gone through so many skills. I've proven that I have, so I can get to the next stage."
Chad Sowash: Well, talk to the difference of screening in versus screening out, because you guys talk about that a lot, and a lot of people might not understand the difference between that. So what is screening in versus screening out?
Ritu Mohanka: Absolutely. So in our industry, we use knockout questions a lot. Frankly, I think it's a really poorly chosen words. It's not about knocking someone out, it's about bringing someone in. So for example, someone's taken a lot of time writing their own CV. Some other people perhaps have used an agent to make their CV completely polished. There is a gap in that first person's CV because they haven't gone to AI to make a perfectly polished, padded CV. They may have not mentioned about communication; however, they may have great communication skills.
Ritu Mohanka: So this is what the AI screening—both chat and voice—does. When a candidate goes through a screening, let's assume they're applying for a customer support role, but they've been a bartender. Most recruiters will look at that CV and go out. Screen out. Why? Because they've never done a customer support role, they're a bartender.
Chad Sowash: That is customer support at its best.
Ritu Mohanka: Absolutely! And this is exactly what this screening technology would do for VONQ, is would say, "Okay, well, a bartender probably does very complex tasks, has to deal with some very difficult customers, has to communicate really well, and has to work under pressure." All the skill sets that require for a customer support role.
Ritu Mohanka: So once a bartender goes through a chat, it ticks off those skills that the candidate has proven or demonstrated it has, which is around communication, it is around being able to handle difficult customers. So when you go through voice, if there are still some gaps left, they will close that gap again so you can screen those candidate in.
Ritu Mohanka: So we're not saying, "Hey, from 500 applications, we're going to dwindle it down to 20 for you." What we're going to say is we're going to help you rank them so you can see who surfaces at the top, so those traditional signals that are now missing, it helps you really unearth those signals.
Chad Sowash: I'm going to get a little controversial here.
Ritu Mohanka: Go for it.
Chad Sowash: In the news, we've seen that Palantir and HCA, they've actually created this scheduling and technology that seems to have gone haywire. So from my standpoint, and as we continue to hear that the Anthropics are going to save the world, the Googles are going to save the world, the recruiting world, talk a little bit about why companies should focus on experts in this space as opposed to looking toward the gods of Google, or OpenAI, or what have you. Talk a little bit about that, because I think from my standpoint, that's what we always hear. We always hear that Palantir is going to come to save us. It doesn't feel that way.
Ritu Mohanka: I couldn't agree more. I think I even think like that about technology. I always believe that the best enterprise technology will be one that is truly embedded, truly connected, and has an agent working behind the scenes. What I mean by that is enterprise technology shouldn't build everything on their own. This is where VONQ's little plug on our hiring API comes into play. What we do is we embed our solutions into 100+ ATSs, the native solution. So we meet where the recruiters are. We have the expertise. We sit at a very interesting intersection between we see employees or candidates, we see employers, and we see all these HR technology systems.
Ritu Mohanka: So we are the specialists in saying: We know how to optimize for distribution. We know how to create the right content for employer branding. We know how to screen, score, interview candidates because we apply those skills and parsing methodology to that. And I think that's why if the Googles or the Anthropics of the world think they are specialists and they can build that, I think perhaps they're being a little naive. But who's to say, who am I to say that?
Ritu Mohanka: But I guess that's why specialist technologies will always exist even if it's a platform, and that's why we've embedded ourselves into 100+ ATSs and HCMs, because we know that those ATSs and HCM shouldn't build what we are best at. And I think they've realized that very quickly. Whilst they'll build a lot, there's certain things they will not build because if they want to be the world's best specialists at something, they've got to rely on other specialists.
Chad Sowash: Well, and that even brings the conversation even closer to home as the Googles, the Palantirs, the Facebooks, or whomever, right? They're not even in our industry. But as we've always heard "best-in-breed" versus "one platform to rule them all," that's an entirely different discussion, but that is very poignant because we always have companies—their dream is to have one platform where they don't have to worry about anything, set it and forget it.
Ritu Mohanka: Totally.
Chad Sowash: But that has never been the case, and I think even more today, it's not a relevant discussion to have. You should be looking for best-in-breed plug-ins, best-in-breed whatever your problem is, there's more than likely there's going to be a solution out there, and more than likely it's not going to be your big core platform that provides them.
Ritu Mohanka: Totally, totally. And I think whether we like it or not, ATSs will always remain the system of record.
Chad Sowash: Yeah.
Ritu Mohanka: And for the right reasons: for structure, for data, for compliance, for governance. So they probably need other systems for systems of action.
Chad Sowash: Yeah, and I think what you're talking about is the applicant tracking system is literally just going to be the record file holder, and you're going to have these layers of orchestration over top of them where a VONQ could be one of those layers of orchestration. Is that what I'm hearing?
Ritu Mohanka: That is entirely what you're hearing. So we are the orchestration layer across 100 ATSs where we are embedded natively, where some employers know we're there, some employers don't even know we're there. When they create a job and they want to post a job, or they want to distribute it, or they want to programmatically advertise it, or they want to create content, or they want to screen, score, interview, that's our technology. Because we do that best. We've got 20 years of experience and expertise in that. We are at the right vantage intersection point of employers, candidates, and technology. And hence, we are the orchestration layer for top of the funnel, and that's where Echo comes in.
Chad Sowash: Excellent. Is there anything that we haven't covered that you'd like to cover?
Ritu Mohanka: Well, I'd just like to say one thing. I know we've spoken only about recruitment and hiring. I think AI is going to be much bigger, and I think that's what excites me every single day. I know I'm very focused on hiring right now, but every day I think, just imagine, everyone talks about AI as automation and efficiency. I want to talk AI about creating that human capacity. Just imagine what it can do.
Ritu Mohanka: So even in my role, if AI can automate 40% of tasks that I do—because what's a job? Job's essentially a combination of many tasks together. And that's the important distinction. So if we can do—if AI can do 40% of my tasks, what does it do for me? It creates that capacity that helps me expand my ambition. And I think that's what I get excited about every single day, that it's so much more than hiring, and AI is so much more than fear or automation and efficiency. It's truly about creating that human capacity.
Chad Sowash: You heard that, kids. AI is not coming to kill us, that's what Ritu says. Ritu, if people want to find out more about you or they want to do a little bit more exploration with VONQ, where should they go?
Ritu Mohanka: Come to our website or follow us on LinkedIn. We have a target of 20,000 followers this year.
Chad Sowash: Excellent, excellent, excellent. Thank you so much.
Ritu Mohanka: Thank you, Chad. It was a pleasure.
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