The Breakthrough Hiring Show: Recruiting and Talent Acquisition Conversations
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Join our host, James Mackey, and guests as they discuss various topics, with episodes ranging from high-level thought leadership to the tactical implementation of process and technology.
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The Breakthrough Hiring Show: Recruiting and Talent Acquisition Conversations
EP 148: AI voice agents and the evolution of recruitment with Kwal’s Co-Founder, David Tell
James Mackey, CEO of a leading RPO provider, SecureVision, and Elijah Elkins, CEO of Avoda, a highly rated global recruiting firm, co-host Kwal’s Co-Founder, David Tell, in our special series on AI for Hiring.
David shares how Kwal’s generative AI voice agent is evolving recruitment for staffing firms and RPOs by automating initial screenings and interviews. The conversation highlights the challenges of bias in AI-driven evaluations and the need for companies to address these concerns.
0:00 Generative AI voice agents for hiring
14:08 Regulatory concerns and AI bias detection
22:00 Future trends in AI hiring solutions
27:00 Broader implications and market trends
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Hey everyone, Welcome to the show. This is your host, James Mackey. Today, I'm joined by my co-host, Elijah Elkins. Elijah, what's up, man? How are you? Hey Daman, how are you Good? And we're also joined by David Tell, who's the founder and CEO of Qual. David, how are you doing today?
Speaker 3:Doing great. Thanks so much for having me on this.
Speaker 1:Yeah, absolutely. And just looking at the LinkedIn profile of your company AI Breakthrough that conducts interviews at warp speed and sounds just like a human the perfect recall and adaptive questioning. No detail gets overlooked. So that sounds pretty cool and we're looking forward to learning more about that. Do you want to start off just with an introduction of yourself and what brought you to founding Qual?
Speaker 3:Sure, qual is a generative AI voice agent for hiring. Prior to Qual, I helped start another company called TaskAid and during that process it's a curated marketplace sold to enterprises effectively, and we had to hire a lot of people at scale globally in about 70 different countries, and it was a pretty challenging environment. Just with the time changes and I always wanted to provide a really great experience to candidates but also difficult to scale that quickly, and so that's the genesis for Qual really is just like living through that pain, and so it's exciting to see that it's built, it's working, it's operating and customers are finding value with it.
Speaker 1:Yeah, that's awesome. That's really great to hear. And now you've been in business. Now what like better part of I think you said what a year or two.
Speaker 3:Yeah, about a year and a half.
Speaker 1:Okay, cool. Can you tell us more about your customers? What types of companies you're working with?
Speaker 3:Yes, typically working with staffing firms and RPOs, and typically we're working with companies that are dealing with roles from anywhere from customer support to nursing type of roles or physician assistant type of roles, so across a wide range of industries, everything again from healthcare to construction.
Speaker 1:Okay. So when you say like, partnering with, like RPOs and staffing companies, like what is it Like? You're there. Essentially your product is replacing the screening call for, so the initial, when RPOs reach out, like how does that work exactly?
Speaker 3:Yeah, so primarily it's going to be the first call is what we would say. In some cases that first call is the entire interview, particularly like light industrial is a great example where there's no secondary interview. So you could say that's the whole interview and kit and caboodle. In that type of industry, other roles, and depending upon the speed of the need of the hire, it might be the first call that happens, but then there might be a secondary call. Really depends upon the customer or the use case.
Speaker 1:Yeah, that makes sense. So my question, more so on the RPO side, is when we plug into a customer, we're representing their brand. So when we screen candidates, it's we're talking as if we're an intern part of their internal team. We have their email address and we're fully embedded, so to speak. So how does that work? Is it essentially, essentially like this kind of like white label situation, which it's like the rpo makes it part of the package that they're essentially selling to a customer?
Speaker 3:yeah, it depends on the setup of the rpo. Some have their own middleware that they work with. Others will spin up, for example, like a bullhorn instance for each end client. Some will use their own middleware that they work with. Others will spin up, for example, like a Bullhorn instance for each end client. Some will use their own excuse me, the clients and ATA system. So it really depends on the RPO setup, but we can support any three of those types of use cases.
Speaker 3:And then in terms of the dialogue and like the tone, the flavor, all those things that are possible now with generative AI, that's where we like hone in with the customer right. A lot of people think that I think this is a misnomer about enterprise sales and generative AI just generally, which is that it's just like a product, just slide it in. But I think that's actually like a massive misnomer. I think a lot of times you're spending a lot of time with the service provider or the customer, whoever that might be really like. What is their brand? What is their dialogue? What do they want these calls to sound like?
Speaker 3:And every customer is slightly different.
Speaker 1:Yeah, for sure. Oh yeah, I'm looking forward to diving more into that. Elijah, do you have any high level product questions you want to cover?
Speaker 2:Yeah, yeah, I'm curious, David. So we've interviewed so far Ben at BrightHire and Mark at Pillar, so both in that interview intelligence space right, they're probably dealing a lot more with like tech companies or knowledge worker type jobs. I'm curious is Qual doing much with knowledge worker screening calls or do you foresee Qual being able to support those more knowledge worker type screening calls at some point?
Speaker 3:Yeah, we already do support knowledge worker types of calls. But just to give you a sense of the entire industry, I think 50% of the market is light industrial alone from just a pure hiring standpoint within the US, of course, just by the sheer numbers. We're going to do more of that, especially specifically like the contingent workforce space. What do you think about? Yeah, can we do knowledge workers and we? And do we do them? The answer is yes, unprivately, we do them, but in terms of just pure volume and where the market is, a lot of this is going to be in the category of things that are not necessarily what we, what you and I might consider knowledge work. And then, as you move up that chain right, you'll see that a lot of jobs are in other areas that are I would call semi-skilled, maybe like customer support, things like that, and I think that's like another, like step function. So when you just think about the overall market, I think that's the biggest predicator of where we will fit in.
Speaker 2:Nice. And how does it so? How does it work?
Speaker 3:Take us through, say I'm a candidate for a sales job or you could say, light industrial staffing job. I spent years working in light industrial staffing when I was late teens, so take candidate depends on the company. But if they are, some companies have an open pipeline and others will have the apply filtration system, typically using something like an ATS, which might have their own version of that, or something like a Daxstra or a Texkernel which was just acquired by Bullhorn, and apply that sort of filter match score, then send the candidates to us. So we're typically not in the game of filtration or identification. We're in the business of execution and thinking about tools like BrightHire, for example, or MetaView would be like another one.
Speaker 3:Those are great tools. We're not competing with those tools. Those tools are really like you can imagine us as probably like an earlier step of that process. But then, right when you actually want somebody internally to actually have a call with somebody to see whether or not they're going to fit within your team, which would be a huge thing is where I think those tools fit in. And interestingly they have their own competitors, right Microsoft and some of the more general note-taking tools. We're not really in that space or that sort of preliminary space.
Speaker 1:Do you see the customers that basically, upon applying their candidates, are immediately prompted to engage in this screening call? Or I was just wondering how frequent that process is, because, if one of the things that I've been thinking through is, just think about the sheer number of applicants, a lot of what I do is in the tech industry, so of course we're seeing a ton of applicants, but whether it may be in light industrial, there's a ton of applicants too. Is that accurate? Just real quick? In light industrial, do you typically see high levels of inbound applicants?
Speaker 3:It really depends on the company's internal strategy around whether or not they want to spend marketing dollars. Typically, what we see so it's more of an internal strategy, but so it depends on the customer is what we see. We also support source calls too. Just to be like clear, if it's not somebody, that's, if it's somebody already internally in the database or somebody that they sourced, we do have a chronic extension that allows people to basically add candidates. That way we're not just a pure apply system, if that sort of gives you a little bit more context.
Speaker 1:Yeah, so that was actually like. Like if somebody there's you want to get to all the applicants, for instance, whether you have a few or a ton, and maybe it just makes sense to okay, anybody who applies can immediately go through this process without scheduling an additional screening call. I'm just curious if you see adoption from customers that, or do they typically want that human touch and review? Do they want to speak to like where, what is? What are you seeing when it comes to that automation around that first step?
Speaker 3:Yeah, that's where I was going with that earlier part was this idea of open funnel, which is you don't apply a filter, Like you have candidates that come in. We do a lot of that where people are saying hey, either the resumes are not of high quality because of the industry. That it is so light industrial is sort of notorious. Like a lot of the resumes are not very good in light industrial. So in those cases, right, it's more about speed and timing and all those types of things to get a candidate in the door working right, and so you don't want to forego an opportunity to filter somebody out that might be like a hidden gem for that type of role. So that's where we see, to your point, this concept of open funnel.
Speaker 3:The other area we see that in right now is for more of these, like I say, mid-skill to maybe knowledge worker type of jobs. You have a flood of applicants, right. So a friend of mine who runs a tech company literally had the other day, within a couple hours, 1,200 applicants, right, he doesn't want to spend time and resources doing that, he just wants to say hey, like a lot of these resumes I can't tell like they've clearly been through ChatGPT and I don't know if this person actually has the experience. So that's another sort of use case that we serve. Is you just have a lot of applicants, a lot of the resumes, look good. How do you like actually whittle through that pile pretty effectively? So it's pretty hard for recruiters to even do, and that's another way that we see this sort of manifesting to your original question I.
Speaker 1:One thing I noticed on your website is you have this I see the evaluation part was like candidate summary and it's like a match score.
Speaker 1:So what's interesting is when we were speaking with a pillar market pillar and then ben Ben over at BrightHire, they actually stayed away from doing matches or actual like evaluation or stack ranking, which to me it's. That is great. I understand the risks they're in and it shouldn't be, we shouldn't be filtering people out. But evaluating match does seem like that's. It seems like an intuitive, uh, important does seem like that's. It seems like an intuitive, uh, important, somewhat obvious part of what should be part of these generative ai solutions and well within current capabilities to some extent. So I'm just wondering it's like I was curious to get your thoughts on that, if you like why did you decide to do that and if you have any insight on why you think maybe bright higher or pillar or some of these other solutions don't do that. I'd be curious to get your thoughts there too, why you think maybe BrightHire or Pillar or some of these other solutions don't do that.
Speaker 3:I'd be curious to get your thoughts there too. Yeah, I think maybe one insight on why they don't do it is because they're maybe more competing with the note-taking space and so scoring may not be as maybe intuitive in that space. Maybe you're really just trying to identify what happened on a call and so maybe that's just the way, the natural way, the industry has adopted. I think In our space, where we're applying more of a secondary filter often, or sometimes a primary filter through a voice call, I think the score probably maybe matters more a little bit for customers because they're using again, in those cases you might only, have, like, with a bright hire, three or four people you might be interviewing, right. So you know, the delta on having a human sort of do a rubric or whatever they're doing is not it's not a large lift, but we were talking about like thousands, right? Potentially, I think that's where a score is helpful, because it's effectively providing some sort of filter. That being said, this scoring is something that's optional, so if a customer asks us to turn it off, we can do that, so we effectively just then start producing a summary, right? So same thing as brain hire.
Speaker 3:The challenge is you're going to have to go through each one of them individually determined.
Speaker 3:So that takes time.
Speaker 3:So it's still less time intensive than trying to place 100 calls with your existing recruiting staff or internal staff, whatever type of business you are. But if you think about it from a time-saving standpoint, that's where I think the scoring happens, and I think one of the reasons is people are nervous about this is obviously the legal implications around scoring. But there's great guidance out there about this whole area and I think, generally speaking, I think regulators are not dumb. I think they understand that it's not exactly like a perfect world, right, like when you have large volumes. This is like what you need to do to be effective, but it's like how you do it, and I think some companies are just going to be farther along on the risk curve, and so I think that's what you're going to see. I think you're going to see a lot of vendors either play very risk adverse others say maybe it's not as important and then others which are like us, which are going to be more adaptive to sort of customer needs and also geographies too, because these rules are not uniform.
Speaker 1:I was wondering. That's where it's too. It's like these enterprise companies there, it seems from a compliance standpoint and a risk standpoint it would seem to make sense as to why that would be a blocker to them, and maybe there's just generally lower adoption to new aspects of process. So maybe we'll just start to see more of it in the next six to 12 months. But I'm not familiar with the regulatory restrictions and requirements for AI essentially doing matching, but I'm wondering specifically what the main concerns are. I know there has to be transparency around, like how I'm assuming how the ai is doing the matching, but I don't. I think one thing that might be a blind spot for me. I don't know if you either of you guys know this, but it's. I still don't fully understand why ai is considered like riskier than having people do it.
Speaker 1:I agree on, I agree so, like I was talking with daniel chate, founder of Greenhouse, and we talked about this and he was like, because it's like the risk of bias at such large scale.
Speaker 2:So he was like if the system's doing it wrong, it could do it wrong with a thousand people or something right, yeah, but every one of your recruiters and HR people have biases too, and at least with the AI you might be able to know what some of those inherent biases are that are going to be multiplied across a huge number of candidates versus. You don't know all the biases of your team and they're all going to be different, so you almost have you know what I mean Like unfair biases, because you don't know what they are. With AI, I'm assuming you might be able to identify with some of what those are. I don't know what you think, david.
Speaker 3:I think you really touched on something that's pretty interesting, which is how many companies you think today, using like a bright hire or one of these tools, takes all those calls and then runs them through an algorithm to determine whether or not there was bias that actually happened on the call. My guess is probably not a lot, but the beautiful thing about where we are with large language models is that a lot of companies that are building in the space they use the LLM as the judge right. These things are pretty effective at judging what happened on a call right and determining if there is bias. So what's interesting is there's so much fear of the bias from the AI, but are most companies even taking the recordings of their actual recruiters today, identifying bias when it's not happening? And I guess the answer is probably there's another aspect to that.
Speaker 1:I don't think companies are necessarily coming out and saying but just having operating with HR tech companies as well, even outside of recruiting technology, sometimes providing analytics around risk and compliance if it's not legally required. I'm not an attorney, but I would say that there could be some concerns there. It's okay. When more of this is brought to light, then we're in more of a position at a risk in terms of needing to immediately address it and solve it. So maybe I have no idea what I'm talking about here, but I'm just trying to think out loud. I wonder if, like part of it's like we're hitting our compliance requirements Right. Do we really want a nice report outlining more than what we need to provide that could be audited, or something of that nature? Does this make any sense? I'm curious to get your thoughts there.
Speaker 3:Yeah, maybe a little bit of background too. I'm actually. I'm an attorney, I'm licensed in California and Florida oh nice and I've worked in a compliance department before. So I could think if there's anybody that might be able to answer this question, I think maybe I'm the right guy. Oh, that's awesome. I'm so happy I asked on this podcast.
Speaker 3:Look, I think companies are not always good at determining, like, what the risk is. There are certain things where it's just super high risk, right, Like you're doing a transaction right and the guys that you run. That's super high risk type of transaction. And I think, for as much as companies have tried to develop risk profiles and things like that over the years and it often involves insurance and risk management, sometimes like treasury it's effectively like a hedge within a business, especially a large business I think that it makes sense why they're risk adverse. It's like a lot of it is. They don't know, they hear things they say, oh my God, worst case scenario. But when you actually look at the entire risk profile of what a business has going on, I actually would put this the way low end of the risk curve the regulators in the EU would say, David, no, you're completely wrong, but I would tell you they're completely wrong.
Speaker 1:It's just weird. What's the big? I don't know. So I was just wondering. For instance, brighthire and Pillar, I was wondering if one of the reasons like they're not doing the evaluation pieces just simply because they're targeting mid-market, upper mid to enterprise customers and they just don't want to, they don't want to make it harder essentially in their sales process, and I didn't discuss this directly with them, but I'm wondering if that has something to do with it.
Speaker 3:so yeah, I think if you think about like the enterprise sales process typically, let's just say that used to be nine months.
Speaker 3:I think at enterprise hr tech that's probably way north of 12 months now 10 years they don't want to risk a sale, so they're going to do whatever it takes to make sure the buyer feels satisfied. And the buyer has to go through a lot of hoops right. Typically in those orgs there's a procurement person, as you guys know, and then there's, you know, it security team that needs to sign off and then typically legal is involved in the process, and those could be like treacherous waters to navigate to get a sale across the line. So I think you're onto something Like. I think that's probably an adaptation to a lot of those like processes, and I wouldn't be surprised if BrandHire goes through multiple committees to get a sale done right. Like it might be, they might have to talk to 16 to 20 people right over the course of that period of time, find the champions and then navigate through the entire process. I think it's a function of the environment that the sales process, and then therefore the product, is adapting.
Speaker 2:I'm trying to think do you see anything with how the tool is developing further with the advancements in AI? Did you guys, once GPT kind of came out, really see a lot more advancement and really launch off from there, or were you working with other tools before that? I'm just curious how that impacted the trajectory of the business.
Speaker 3:So the first company that I helped start is called TaskAid, but it's still around. It's a Series B company. The search engine there is actually developed on transformer architecture, so pre-GPT. So it's called BERT. It's very well known. It was Google published it and made it open source, and so we basically built our entire search function around that, so we're very familiar with transformers. The company really started around time of GPT-3, prior to chat GPT explosion, which is 3.5. So, yeah, this was an evolution, right, like in terms of is the technology mature enough? Can it do all the things that we want it to do? Because there still are a lot of vendors in the market today that are pre-generative AI, that are based on the old piece workflow builder right, if this, that it still has some AI elements in terms of it's like it's transcribing, which is certainly part of AI. It's doing some natural language processing, some intent detection, but it's not what we would call today a generative AI driven system or an agentic system, which is like a further step up past this generative system.
Speaker 2:And have you seen with your customer base as they implement Qual and start getting value from it and let's say they are using the score, as you mentioned earlier, are they reducing the number of assessments like later in the funnel, like if they're using, like a metal or some sort of assessment platform, personality or what have you? Was that providing enough value on that first call that they're reducing those assessments down the funnel?
Speaker 3:Definitely so. In the case where there is an assessment, for example, like a classic one, also might be like English language assessment, right, others which can be more technical assessments, clearly it's acting as a sort of filtration step. So it's pretty interesting because there's a lot of companies that are in that space, like iMocha and Glider, and they're going to be. You're not going to send a thousand candidates to those. They're just typically too expensive or too time consuming. You're not going to want to put candidates through that. So, yeah, qual acts as a great sort of again filter step before you would send somebody to an assessment. But not every role requires an assessment.
Speaker 1:Cool, yeah, I was curious. So, david, I'm curious to get your thoughts on how you're thinking about the future for Qual over the next six months here, if you happen to know what you're going to be building over a year out. But just say what feedback are you hearing from customers? What additional functionality do they? What use cases do they need help solving? What's next?
Speaker 3:Yeah, I think the biggest thing that we're going to move towards is we're obviously a voice solution. We do SMS and email and voicemail, but I think the real future is like what I would call intelligent agent, omni channel, and so we're driving towards that. It's not just about a call happening and being bidirectional or text being bidirectional. It's like how do you tie all these things together in a really intelligent way? There's a lot of older solutions that sort of claim that they do this, but again they're stringing things together and like duct taping them. But I think the real future is like how do you merge all these channels so it becomes like a single channel and the agent is like the back plane behind that right, this idea that you have access to the logic, the, the memory and the tools and functions that agents can have right to execute different things, whether it's on a call or whether it's a text. So I think that's the future that we're going to drive to and I think that resonates with a lot of customers that we talk to.
Speaker 1:Yeah, it makes a lot of sense and I know you said most of your business is on the. It sounds like a lot of your customers on the RPO staffing side. Do you see that growing also into like more in-house companies or what's your?
Speaker 3:Yeah, I think so. I think so. If you look at RPO, rpo is typically hired by an enterprise and staffing is typically hired by enterprise. But I think it has to make sense. Do they have this sort of volumes? We're probably not a solution for a two-person type of shop and also from our standpoint, we really like working with RPO and staffing. We think it's pretty dynamic space. We get to see a lot of different things working with them because they typically have more than one customer. So it's a great channel for us and I think we'll spend a lot of time in this space. But as we sort of grow and all those types of things, obviously engaging directly with the enterprise is something that we will take on if there's mutual interest.
Speaker 1:Yeah, makes a lot of sense and suppose, do you like just talking about the future of AI and hiring, maybe even a little less related to the use case that you're helping your customers solve right now, to the use case that you're helping your customers solve right now? Curious to get your thoughts on other product plays, other use cases that are technically feasible or will be technically feasible to solve for the next year. Curious to just get your general thoughts on our space, so to speak, and what you think is coming over the next 12, 18 months.
Speaker 3:Biggest thing is going to be outside of what we're doing is going to be in the browser-based space, browser agent space specifically.
Speaker 3:You can think about that as executing a query right, and then the agent is going to go log into your LinkedIn right, go, click through profiles, determine whether or not this person's a good fit and then generate a report for you or like a list. I think we're going to start seeing that there's been a lot of companies out there that are built chrome extensions and stuff like that, or they work with people data labs, as an example, and these like large, like list building companies similar to, like, zoom info, but I think the real thing is that those are typically like stale, oftentimes right those databases are. They have to get constantly updated. A lot of that time that's happening from humans. But I think this idea of these agents that can actually act on your behalf, like on your browser, like execute the task of identification of candidates it's going to be really big. The curiosity I have there generally is like how is indeed, or these types of companies in a or linkedin, yeah?
Speaker 2:are they gonna block it? How are they gonna?
Speaker 3:block it. Um, yeah, they've clearly done that with, like, the scrapers. This isn't typically a scraper, right, it's a lot different type of technology and so I think there's like some questions around that and, yeah, probably we'll probably see some lawsuits at some point for whether or not people really have permission to do that if they. But it's interesting because it's like an extension of you, right, these agents, right like the whole concept of the agent is you're the principal, that's the agent, just like hiring a contractor, right, and it's sort of the same idea, except it's a digital entity that's doing that. And I think that's where this is going to get really interesting.
Speaker 3:It's like, how many of these tasks can we offload today that were really painful?
Speaker 3:And I think it's really great for recruiters that actually want to be connecting with candidates, right Like selling candidates on roles. So I don't look at it as like there's probably a lot of fear about AI for, like, recruiters and sourcers and a lot of folks, but I think if you're in the business of selling roles and culture like that's not going to change, like an AI is not going to do that. But I think that recruiters that really also understand the nuances of the business, right, like the end business, really are engaged and understand like that piece of it. There's a moat there, right, and AI is not going to come in and replace that, but these sort of ancillary tasks that people are conditioned to doing because it's just the way it's been done, I think that's where AI is going to be really disruptive, and I would expect that we would see either two things happen. One is you're going to have a smaller amount of recruiters or you'll have the same amount of recruiters, but the service level quality will just rise, and I don't think that's a bad thing.
Speaker 1:Yeah, I mean, I think that's spot on. I think the role of recruiters is going to change drastically. One of the reasons we're doing this series and one of several is, I think talent acquisition leaders, probably more now than ever, are getting very interested in the technologies that are available in the market, which is funny because it's happening at a time where they really don't have the budget. But I think that the best talent acquisition executives are going to ultimately be ones that understand how to leverage these different products and, essentially, the right balance of technology and people and how to most effectively, based on the nuances of their industry and their business, have those things that integrate, those pieces integrate. That's going to be the core skill set, and this is probably the case of most departments within a company, right, but it's going to be the core skill set. That a great, and this is probably the case of most departments within a company, right, but it's going to change.
Speaker 1:It's not going to be good enough to just understand process. You're going to have to understand the nuance of, based on your business, your candidates, your hiring goals, what should technology solve and what should people solve, and what parts of the process and and whatnot, and how to incorporate those things in a way where you still get the visibility you need from a reporting perspective and the integrations you need and to make things run smoothly and, of course, as we discussed, like the compliance aspects as well. So it's going to get. I think it's just the role is going to, of course, get like more, more technical than it's probably ever been before. It's not going to just be like, okay, slap on an ATS, it's okay. We really got to be thoughtful of our process and where we're leveraging tech and how.
Speaker 3:Yeah, I think people are scared of this. I think again because it's a new level of automation. They haven't seen it before. They used to be the person that would spend 30 minutes building a job description. Now it takes about 10 seconds and you can imagine every ATS is building this if it doesn't already have it. We already have it. It didn't take very long for us to develop. So I think those are the low-hanging fruit, but there's quite a bit of fruit everywhere in this tree. It will shake out, certainly, but we've had automation for a long time. Email automation is something that we've had automation for a long time. Right, like email automation is something that we've had for years. Right, recruiters hit 10 different checkboxes and the 10 candidates get the rejection email at the same time, or it's automated completely. We've had this automation. I think it's just now at the point where we can generate personalization. We can generate things at the edge of the node rather than the sort of like centralized function or centralized matter that really makes generative AI and agents again, which is like a next level past that, like super unique. It'll be a very large learning curve, I think, an adoption curve.
Speaker 3:I think the nature of any sort of transitional change is that there's going to be, like early adopters, people in the middle, the sort of late. But this is not one of those trends where I would want to be late, for I would if I was a leader. I would be evaluating things like constantly, like multiple products a week, because the space is changing really fast. It's still going to be a competitive war for great talent. Always, or even in areas where you might think it's like a blue collar role, some of those are the most competitive, right? You wouldn't? You would be surprised, right? There's only so many people that can do this role and 30 miles outside of Wichita, kansas, that's a really specific role. So I think we're just going to see this adoption happen. But the companies that really move fast are going to be, they're going to get amazing yield very quickly and they'll realize the value. And I think the laggards are really going to struggle, like really going to struggle, and that's why it's always great working with people that can see the future For sure.
Speaker 1:Look, this has been really, really insightful. I appreciate you coming on the show. Is there anything else that you want to share with the audience about your product or anything else? We've got a couple of minutes here.
Speaker 3:Anything else you want to share. Yeah, I think the biggest thing to share is just whether you're evaluating like our technology or a different vendor. It doesn't matter the space, maybe it's not even recording, maybe it's sales or whatever the types of tools you're looking at. Look at when these companies started always right, I think you know. If you're looking at companies that started three to five years ago, right, typically what you're going to see is they're adding things on. But what's really nice about the newer companies that are coming out is that they're all AI native companies, right. They're built from the ground up being AI native and the experiences will be really different.
Speaker 3:So, even though the end product might look similar, the marketing might look similar, the actual experience when you actually dive into these products are very different, and the only way to do that is either getting on a demo call, right? So I would say to leaders that are listening to this podcast be open-minded, right. There's a lot of great new software that's coming to the market. That's completely changing the entire paradigms, from what we're seeing and being aware, meeting the founders, ceos of these companies, I think it's a great thing because you'll get, even if you don't decide to purchase, you get a sense of what is coming and you can be knowledgeable about that and share that with other people.
Speaker 3:And I think, again, going back to what I said earlier, you don't want to have your head buried in the sand, right? You've heard that expression before. This is a biggest revolution, I think, in my opinion, since the birth of the internet and prior to that, probably semiconductors, which is so you don't want to miss out on this trend and you don't want to be under your head buried in the sand, even if you're not going to purchase. Go out there, be curious, meet people. It will only benefit you and your organization as you go through these motions, and it's time consuming, but it's important.
Speaker 1:Yeah, I totally agree, Elijah. Do you have any other final thoughts?
Speaker 2:No, I think David's right. I think you need to keep a pulse on the market to be a good TA leader, and I think we're going to see that more people may be in like recruiting ops, like we saw with, like sales ops and rev ops. Thinking about the whole tech stack, I think the tools those AI native tools that David's mentioning are going to make the TA leaders like tech stack a lot more yeah, a lot more like powerful and intelligent and we'll be able to do things that we weren't able to do previously. But we're definitely still a lot of catching up to do compared to the tools that, like sales leaders have at their disposal to grow revenue, to grow the company and find great people to join the team. There's a lot of great tools out there, but, yeah, probably not near as many as there are in like the sales world.
Speaker 3:Yeah, literally sales. If you think TA is busy in HR tech, sales is just like incredible, like how many tools come into market every day.
Speaker 1:I feel like a lot of hopefully not in the songs, maybe that sounds mean, but a lot of them went out of business. It was just too many. Lot of them went out of business, it was just too many. There was too many Me Too products in sales. Like how many different products that do the same thing? Do you need, good Lord, some categories? You'd have like 30, 40 players, like early stage companies, essentially doing the same thing.
Speaker 2:The pricing's interesting too. Sorry, david, I was just going to throw out there. Sales tools often are a lot more affordable than some of the recruiting and HR tech tools that I've seen. Probably a whole different podcast episode. But the pricing difference maybe that's like you're saying, james, the number of competitors. But an email sequencing tool, for example, you could get for, let's say, $20 to $50 a month for a license, some of the recruiting versions to do email sequencing or anywhere from what 150 to 300 per license and they often don't have the same feature set either, like they have fewer features.
Speaker 3:So, anyways, what were you gonna say, david? Yeah, I've definitely come across orgs where it's especially smaller orgs maybe you guys have where, like hubspot is like their recruiting tool, it's like they've taken a sales tool or crm and like HubSpot is like their recruiting tool, it's like they've taken a sales tool or a CRM and like have tried to like build around that. It's sort of interesting. But I think there's just a lot of orgs that, in my mind, probably don't want to deal with the complexity of again duct taping things. So I think that's probably why you still see higher rates and I don't think that TA is not a competitive market or recruiting tech is not a competitive market. It definitely is.
Speaker 3:But yeah, I think sales is just it's revenue driving function and I hate to say that as an HR person, right, every TA leader would probably like yell at me right at the top of their lungs no, we're a revenue generating function and it's true Like HR is responsible for finding people and engaging people and retaining people that are in revenue driving positions, and it is all about the people. There's no doubt about it. But I think, if you think about from a sales perspective, if you're selling a tool, most people want to sell it to a revenue generating function. Right, it's pretty, pretty much that's why that is, and so you're always going to see the most amount of tools that are going to probably drive revenue or give you insights into revenue, which is why you see so many of these tools that are to your point, like RevOps tools and analytics tools. It's just like the numbers are just like staggering in terms of how many there are out there.
Speaker 1:Yeah, it's just, I don't know how you expect to scale an incredibly successful company if you had 20 competitors doing the same thing, but I don't know. Anyways, yeah, the market corrected, hopefully is doing the same thing, but I don't know. Anyways, yeah, the market corrected. Hopefully it's not as saturated now. But anyways, we digress. We're coming up on time here. David, thank you so much for joining us today. We really appreciate you coming on with us on the show.
Speaker 3:Yeah, it was a lot of fun. I really appreciate you guys having me Great dialogue and I look forward to staying connected, and our company website is wwwqualai for those that are listening. And yeah, I'd love to just talk to people in the space and see how we can help you.
Speaker 1:Yeah, that sounds great and we're going to put everybody tuning in some notes and descriptions so you'll have the website, david's LinkedIn profile, all that good stuff. And, by the way, yeah, david, if there's anything you want us to drop in the show notes, just let us know.
Speaker 3:For sure Awesome Cool.
Speaker 1:Thank.
