The Resume Is Dead | Show Me You Can Actually Do the Job

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Speaker B: Hey, this is William Tincup and we are doing the Use Case podcast with Ellie from Kanatech. Ellie, how are you doing?

Speaker A: I'm doing great. I'm excited.

Speaker B: You are excited? Well, let's not disappoint. So, uh, tell us a little bit about what you do at Canetech.

Speaker A: Yeah, sure. Well, first of all, thank you for inviting me along. It's absolute honor. Um, so I'm Ellie. I am currently the head of customer success at Candy Tech. I've been with Candy Tech for four years. Um, basically how I would describe it as I really help our clients to see how candidates do the job before they get the job. Um, so I'm very involved with day to day conversations with our clients. Uh, everything from an early initial, um, discovery calls all the way through to implementation and also long term account manager. So it's really great because I get to see the, the before, during and really uh, have worked with many of our clients for many years. So sure, that's what I do in a nutshell.

Speaker B: So for the audience can attack what if you're explaining it at a party or whatever, dinner, how would you explain it?

Speaker A: So Candy Tech, we are many things but ultimately we are an all in one skills assessment, job simulation platform. Um, so we really help clients um, evaluate their candidates. Hard skills, soft skills, of course, AI skills, cognitive ability, personalities, video interviews, uh, everything really all together mostly through uh, realistic job simulations that are really designed to mimic the job as closely as possible. Usually a very early stage of the hiring process.

Speaker B: And then are the simulations, are they off the shelf? Are they custom made? What does that look like?

Speaker A: All options we do. So we have a very, very large library. So everything is overseen. We have a team of expert PhD holding psychometricians. So their whole job here is to really support um, our library, our growing library, um, many, many ready to use sections. Everything from engineers data, um, roles to HR admin, customer facing roles and everything in between. So, so we have in the library, our users can take directly from the library. Um, they can also fully customize everything from the library. So if they like it, but they want to Change it, Make it more relevant for their use case. They absolutely can do. But of course, they can also build, uh, their own tests from scratch. And we also support our clients for implementing home tests. A lot of companies, uh, already have home assignments floating around somewhere, some rules. So we can also implement them into our platform so they're checked and scored automatically, um, branded, integrated with the ETS and, uh, all that good stuff.

Speaker B: So are your customers asking you about, let's say, agility or people that are good with ambiguity or potentiality, things like that? That's kind of nebulous in a sense. It's just, uh, I'm thinking about, uh, a discussion I had with a chro two weeks ago, and she was just saying, listen, the job that you posted that you put all your hard effort and work into, that job's gonna be a job for about six months.

Speaker A: Okay.

Speaker B: And then it's gonna be a different job. So you're gonna need people that kind of roll. Like, okay, yeah, that job. Great. Fantastic. Now what we need you to do is this. And we'll help you build your skills for that. Like, we're not just gonna leave you there. Um, but it's. She was talking about, I need people that are super flexible. Like, yes, they have some skills. Great. But on some level I can teach them the skills once we learn what the new job is, but I need them to want to change.

Speaker A: So really great questions, I think. Ah, there's a really big mix. I think that's very true. When it comes to working with, uh, early careers, um, they're really looking for a potential, uh, like hiring potential. You know, they're not expecting candidates to be able to write code or optimize marketing campaigns, etc. They're looking for someone with good attention to detail, someone with good, um, core intelligence, critical thinking. And we do have a library of very typical cognitive, uh, skill sections. Critical thinking, numerical reasoning, um, attention to detail. Um, but the vast majority of our clients are even when it is early careers. And they're looking for that sort of. I don't like the word unicorn, but you know that. Yeah, yeah, that's malleable. It can teach skills, can pick up things, uh, quickly. Um, but they're also looking to see that a candidate can come and hit the ground running. And I think now, especially with, uh, AI, you know, I can take a job description and I can give it to an AI and I can take my resume and put it in AI and say, make this much that maybe get through any ats, cv, parser that there is it doesn't. And so the trust that, uh, you know, recruiters and hiring managers maybe once had, um, with, um, with resumes and what they see on paper, it's beginning to be a little bit broken. So they're, they're looking to see how they can have their candidates demonstrate that they can actually do the job. But yeah, those are really a whole mix.

Speaker B: I've always thought that people lied on resumes and LinkedIn just in general, not overtly. You know, like, I, like I never had a job at that company and I put it on my resume. I don't think it's that. I think it's just the embellishment, the little things. Like I was a part of a sales team that brought in $200 million. Now I did one thing, you know, on one project and you know what I'm saying, But I'm gonna take credit for the whole 200 million. Uh, it's true, but not really true. So that's, I think, getting to the point of verifying. And so Reagan President, uh, Reagan 100 years ago said, uh, this famous phrase, trust but verify. So, uh, he said it was something completely different. But, um, I think the verification process has gotten more. There's more of an onus on hiring managers and recruiters to verify that these things are actually true.

Speaker A: Absolutely. Like, I think there's a huge merit to like, you know, applications. I think the average job, I mean, obviously it depends on, you know, the different, you know, company, etc. But there's over 100 applications at least, um, for roles. And so there's a merit to be said for candidates standing out from the crowd. And as a film making, sure, you know, that your, your resume or CV is going to get at least, you know, read. And I think the statistic is that, you know, CVs and resumes get, get like eight seconds of a view. And so I think if, if that

Speaker B: uh, there used to be a heat map and uh, and it, it was almost heartbreaking because, you know, you put so much time and effort and put it, you know, your experiences, all this stuff together, it's like eight seconds, eight seconds in a long time. Uh, your name, your email address. Okay, moving on. So it's, it's better on the employer side now, I think, because they are going through everything now. A bot or AI is going through everything, but they're going through everything. At least.

Speaker A: It's true. It's true. I think, uh, what's also really nice is that someone might have really amazing skills and be Absolutely terrible at writing a CV or a resume. And one of the things that, you know, Candy Tech or our clients are able to do is really open up the pool. You know, let's say you have 100 candidates in your pool and 10% are, you know, absolutely no, 10% maybe too qualified. Like, how do you get through that? 80% that are less. And this is one where having a standardized test, especially early on the process, can really help. Not only, um, help you really evaluate and have your candidates, you know, put their money where their mouth is and show them, demonstrate that they can do these skills, but also really helps to unlock hidden talents. Maybe people that, at a first glance, this is feedback we get all the time. Like, you know, I wouldn't have hired

Speaker B: this person, wouldn't have looked at them.

Speaker A: M. Yeah, exactly. And that's a really, like, it's very heartwarming, like, aspect of, like, really giving everyone a really fearful chance to put their best foot forward at a time that suits them. The same chance as everybody else, marked against the same criteria as everyone else. Um, and I think that's really, uh, a really beautiful thing, and I think that's a bit of a trend, is we're going to see less trust, if I could say that, on resumes and CVs, and more onus on can they demonstrate it? Are they ready to come and hit the ground running? Are they going to be able to, of course, adapt to a new, modern 20, 26 and beyond workplace where, you know, I'm sure you talk about this a lot on the podcast, but AI skills, like, they're the center of everything really. Ah, it's a new skill, and not just from clients that are looking to, um, employ new employees into the company, but also looking at their existing workforce, uh, and saying, okay, where are the gaps? Where do we need to evaluate, where do we need to do training, etc. To really make sure that everyone can optimize themselves in a way that AI, uh, allows companies to do.

Speaker B: Do you have customers that talk to you about, are we screening in or screening out? Like, with a test? Tests have always been kind of associated. Um, whenever we test someone or assess for someone, um, some people think of it, some recruiters and hiring managers think of it as we're screening in. And, uh, I think the vast majority of candidates would probably tell you that actually they're screening out. So you take an assessment, you take a skills thing. If you don't hit the mark, whatever that mark may be, you're out. So they kind of see it one way and the hiring folks can see it a different way. But what are your customers when you have you had that question?

Speaker A: So it really, really depends. Like we work with so many clients of all different types of use cases from like huge NASDAQ treated giants like Monday.com, wex, Fiverr, to small growing startups with 10 people and beyond. So it really depends on how many applicants are coming. Like the majority of our clients I would say have too many candidates that they don't know who's the ones I should bring on this. There's never a replacement for the human, you know, face to face, zoom to face experience. But it's just unrealistic for people to be able to give that, you know, face to face experience with every candidate that looks good on paper. And so they're looking for a way to be able to identify early on who the ones that we should be bringing in for the next steps. That said, we also have some companies that are looking to expand their pool of candidates. So what they're doing is putting a short challenge, a 50 minute challenge, let's say, on their career site and they're saying, oh, you think you've got what it takes to be our next customer support superstar, our next data analyst, whatever it may be. And they're actually able to use candy tech to kind of source candidates and have like an open application. So we see both use cases. But I would say really what it really depends on the volume of candidates. Um, but yeah, it's a really interesting question. A bit of both.

Speaker B: A little bit. Probably a different perspective too. So, um, with your, you know, job simulations, um, does the candidate get anything from. That would be the question that I would ask.

Speaker A: So do you mean by that do they, do they get any results? Well, or do they, what did they get? What's in it for them?

Speaker B: Yeah, I think it's okay. So I'll give you some context. So, um, for years people would do like background checks, right? So like you want to apply to shop, Great. We got to have your permission to then go run this background, uh, check on you. And they would provide nothing to the candidate. They would just basically give us your permission. We're going to go do this bit and I'm speaking about you. The, the U.S. uh, there's different laws, different countries, um, and the candidate got nothing. And then there was a movement within that whole category to then give them a copy of what they found. So we did a background screen and here's what we found. You have a copy. Um, and so we've seen that also in some of the testing platforms where you do you run a test and then it grades you out and tells you exactly where you did really well and some of the things that you could learn or, and do better at next time, et cetera. So with, with a simulation, the, the question is I know what we get on the hiring side, employer side, uh, what is there anything that they get.

Speaker A: So in terms of the results. So by default we do not share any results with candidates. And the main reason we do that is because, let's say I want to work for your company and I do a candy tech test and now I have my results and I want my friend to come work well, now I know how I did and how I'd answered and how I did well. And so over time, um, the reliability of the test is degraded. That said, our users are free to do whatever they like and some of them do choose to share the screen. And what's really nice about job simulation rather than, let's say a gamification game where I'm clicking some buttons and it's going to tell me if I'm a great this, that and the other is now the recruiters and the hiring team actually have work sample so they can actually go through. And we have a special mode, um, which is designed to take, it takes away all the sensitivity like scoring comments, anything that you wouldn't want the candidate to see and it just leaves the questions, answers, etc. And they're able to actually have a very interactive interview going through the work sample with the candidates. And it also helps really prep them for any upcoming interviews because now they know where they did really well. Maybe there's some areas they want to discuss, what was their thinking behind this, and so on and so forth. So you actually have a work sample that you can go forward into an interview with. And they do sometimes choose to share these insights with the candidates, but by default, um, we don't share them again

Speaker B: just for, uh, you know, I can, I can. Yeah, I mean that totally makes sense to me. I'm thinking that, um, they also get something because of the simulation, just in general, they get to see kind of behind the scenes they could see, okay, what am I really going to be doing? I'm going to be doing this. So they might have had had an idea of what the job was and all of a sudden then they got into the simulation with, you know, I don't want to do this. Great, good to know. Stop, now leave. I mean, it's Actually a good thing. Uh, I tell hiring managers, recruiters all the time, but like people that go through your process and don't want it, the job is just as important as those that do. So whatever you can do to kind of give them the information, uh, and the ability to kind of make a good judgment or a good call themselves. Great.

Speaker A: Absolutely. I think uh, that's a really, really uh, important. You know, when you first asked that question, I was thinking do you mean kind of like uh, out of the box, like what do they get? But yeah, 100 and a lot of the time as well as like helping our users like generally the day to day of the, the platform, etc, it's also about like we have a huge, huge like professional services and um, side of the, of the, of the platform and, and part of that is also helping our clients. How do we position this? Where do I put this? What stage in the process? How long should the test be? And something I always mention about positioning, candidate positioning is you're absolutely right. Like when it's a job simulation, it's really a chance for them to have a realistic preview of the type of tasks and things that come up in this role. Um, and we have some clients that have a lot of fun with this and they call their tests, you know, an hour in the life of, you know, at uh, company X and they'll have three sections, M. Morning, afternoon, just before just about to run out of the office. And they have a lot of fun with it. And the feedback we get from candidates is that's really fun. But exactly as you said, they also got a chance to see, okay, this is something that I really do want to do. This is something that I maybe don't want to do. And it does give the candidates an opportunity to opt out.

Speaker B: Yeah, I think it's. We pre. AI uh, we would do a day in the life. So we bring a candidate, you know, usually really far in the process. But before we do an offer letter and before we say yes and they say yes, we'd say, you know what, everything's been great over the phone and these in person interviews, everything's been great. Why don't you come and we'll pay them. So why don't you come for a day and just mirror everything, Just kind of walk, be in your group, be in your cluster, go to meetings, do the bit and just see if you see yourself in this job because so, so much of it can look glamorous from the outside and then all of a sudden you get on the inside and you're like, yeah, this, this is horrible. And, and that, that's, that serves nobody's interest because they spin out in a, uh, month or so and go get another job. And we've already invested all this time, money and energy and then maybe even some training. And it's like you're really trying to get to fitability, fit for both sides.

Speaker A: Yeah.

Speaker B: And informing both sides so that they both make, both make the right, best decision that they can. So pulling down those walls or those curtains or those veils or whatever the bit is, it's just letting them see like, can I see myself flourishing in this environment, thriving in this environment.

Speaker A: So 100%. And that's when, you know, customers say, you know, how do I really, like, what's the best thing I can do in the assessment? And it's like, what are the most important? Like, what are, what is the realistic, like, what are the most challenging parts of the role? What are people expected to do in this role? And the way that we can really build the highest predictor of future job performance is putting all those things into an assessment. Um, of course there's always a balance. How much can you fit in the assessment? How long do you want the assessment to be? But for example, maybe you know, you need the candidate to be able to optimize data in a data sheet. And that's great. And we have a really cool question type for that bit of Google Sheet Excel. But that's never the only part of the role unless the rule is literally data entry or, you know, that. And so it's a follow up email. Maybe I want to, okay, can you do the rest? Can you do the calculations? Amazing. Now can you identify the rest? Maybe it's a customer facing aspect. You know, write an email to your client identifying the rest or you know, know, suggesting action items. Um, and then maybe the second section is, you know, the customer's on the call and they have to answer a video question, um, you know, what they would do to prepare for the call or opening questions. And maybe the next section is using our embedded ChatGPT. And you know, your manager's just asked you to, you know, fill out these three, uh, three documents and you've got five minutes to do it. Feel free to use the embedded ChatGPT. So simulating, what does actually this look like? What are the challenges? It's really nice because, because of the level of customization, um, that we can support. It's not just about this role in general, it's about this role and this team with this manager, with these projects coming up. Um, and that's something that's pretty unique and why I really love working with job simulations and I think it makes so much sense. Um, and, uh, yeah, really, our clients get a lot of really, really great

Speaker B: insights, I think in this. You're not saying this. I'm saying this. So just for the audience to be really clear, I think you put the worst parts of the job in front of a candidate. Because for me, there's no shock, uh, at all once they get the job. They know, like that bit where you did what, you talked to a customer, you listen to a video from a customer and you type out your response. Like, I want that to be an angry video.

Speaker A: Oh, yeah.

Speaker B: You know, I'm saying, like, I want to, I want to pressure test on all the negative, every negative aspect of the job because it's easy to sell the positive stuff. It's easy to sell the, the easier task. The, you know, the, the things that are just, you know, the, the. I mean, it's like anything in life, right? Like, it's. You want them to kind of like. I want to understand, first of all, you want to, as a candidate, you want to understand the challenges and whether or not you like those challenges and you want to be a part of those challenges. And I want to know if you can handle those challenges. So I know that you didn't say that, but that's how I would set it up is I would look at that particular job with that particular team at that particular time and all of that, um, to then say, what's really the biggest challenge here? And then I'd build around that.

Speaker A: Absolutely. I think, um, you know, when I have, let's say, discovery calls, everyone has completely different things that they're trying to solve. Maybe it's reducing people higher, evaluating AI skills, reducing, um, unnecessary interviews, um, but also a question of retention. Like, how do I make sure that people are staying past three months, six months, nine months, how do I not only make sure that candidate goes and passes the interview and starts the job, but also stays on and becomes a leader and, you know, is able to, uh, pass the probation and go on to be leaders. And the really nice thing is, like many of our clients have been working with for years and years now, and they choose to share post hire data with us. And when we do that, we can go back into the microdata, the test, and we can say, okay, this is what goes on, not just to get the job, but go on to. This is your DNA of Superstars within your company, um, over years, like really optimize things and make sure that, and you know what's going to look one way for one role and one position is going to be completely different, more like a senior hire and so on, so forth.

Speaker B: So as uh, it should be because there's different stressors, there's different pressures, there's different outcomes, there's all of these different things. So if we cookie cuttered uh, it would be at our own peril. Um, I think one of the things that's fascinating or could be fascinating and your clients probably are, are, are thinking about this yet, but is going back and asking the candidates that went through that test six months later, how could that test have been or how could that assessment or simulation, how could that have been better? So we can learn from them after they've done the job for a while. You know, it like I, I think we should ask them at the end of this simulation, uh, what do you, you know, what do you think? Give us a grade rating, you know, all that type shit. But I mean like I want to know that like because you have access to the data once they do the job for a while, hey, think back to that simulation. What could we have done to make that better? And them now doing the job gives you some insight into. Yeah, uh, throw that away and then do this, like ask these questions.

Speaker A: It's really interesting. So um, in terms of candidate feedback, so we always offer like we always start with the Pilot 3 Pilot. And as part of that process a lot of our clients have a little box that they in for the candidate, hey, what do you think of this test? Etc. And so they are able to really capture feedback that way. But also in terms of getting started with benchmarks, so hiring managers and recruiters, sometimes, you know, they think okay, well these are the main things of the role. And then what they do is they send it to people on the role. And it's really important you say to the people on the role. We're sending you this test. We want to hear your feedback and thoughts. We're not tested like this isn't a real test. Um, but it's really interesting because the feedback that these um, control groups or you know, these um, testing uh, groups is sometimes it's, you know, this was perfect and sometimes it's like hey, this was good. But this is actually not realistic to the how we're doing it today. And this is really m important and I didn't see anything in this. So it's really nice when you bring like the team and because everyone maybe, you know, maybe not everyone but I feel like uh, sometimes different people within the organization can experience what a role type might be differently and so it can really, really become like a very collaborative, cool um, project to do as well.

Speaker B: Right. So you mentioned implementations earlier. So give us an idea of what that looks like. Uh, obviously your connecting process and technologies and things like that. But for the, for the candidate, for the prospects that might be listening to the call. What uh, does that look like?

Speaker A: Yeah, so honestly like with instant implementation times like the platform is super, super, super easy to use. It's a fully self served platform. Like everything that our team can do, our users can do directly on the platform. Um, and some of our clients love to get stuck in straight away and others, you know, fully professional services with our team of experts that can implement custom assignments, create new assignments. We've also got an AI builder inside the platform that can build custom tests based on job description. So a lot of cool technology but honestly we can open up the uh, pilot accounts pretty much instantaneously. Um, depending, depending uh, on the timeline. Sometimes users like to explore for the first few days and then we have a bit of like a pilot onboarding because when you do an onboarding beforehand nobody has any questions because they've not logged into the platform yet. Um, and so a lot of like the getting, you know, the main assessment set up, um, integrating with the ETS work integrated with over 48s platforms. Most of them it's copy this, paste that and the integration is there. So in terms of the implementation we can usually get uh, up and running very, very quickly. Um, in terms of, you know, once we go live for example, there's usually it's one to two weeks. The first week again is sort of tweaking, finalizing the assessments. As part of that they'll send out either to candidates or to these um, sort of groups of people that are already in the role, gather feedback, make the tweaks. Um, so usually the first week or so is just in sort of fine tuning the assessments and also training users. Hey, this is the library, this is the AI builder. You can just upload this. They can also just send their test directly through the platform to our team to implement. So there's lots of very um, easy to use, like it's not a very complicated product, it's a smart product, deep product. There's lots of really cool stuff we get is it's really easy to jump in and get started right away.

Speaker B: Uh, the best software in Our space are like ducks on the surface of water that's very calm and kind of everything kind of. But underneath the water there's a bunch of stuff that's going on. Um, as a matter of implementations, if they're not a member, um, of one of those four 40 ATs's, what do you do?

Speaker A: So the platform is also fully standalone. You can use fully standalone, uh, platform. Um, so instead of the invitations being sent via the applicant tracking system, they're just sent either via direct link or you can send invitations directly to your candidates through the platform. We're, um, also integrated with lots of, uh, connectivity. So even if we're not integrated, let's say it's a custom ats, we can usually do light integration. So we have a team of superstars who absolutely have to have their shout out that are very, very, very, uh, good at their craft and can usually get, um, some sort of automation done for no matter what the, what the use case is.

Speaker B: Most of the, most of what they care about is the data ends up back in the ATS at some form, uh, in some way or another. So how it gets there, um, you know, some people are really picky about that. Most, most recruiters aren't. They just know that it needs to be in there. Um, so the simulations and some of the kind of strategy around, um, what candidate gets what they get, etc. Do recruiters, are they the one kind of the main drivers of that or the hiring managers?

Speaker A: I would say that what usually is the case that in organizations, some hiring managers have tests, some hiring managers don't have tests, some have tests that the recruiters aren't aware of. And so they're looking to standardize things, they're looking to have visibility of things, they're looking to make sure that there's no rogue assessments that are being used that maybe are very outdated. And it used to be the case that to make a job simulation required a specialist. It was very difficult to do. They'd be manually scored. And now it's super easy. You can just take the URL from the job description, put it into the AI builder. Boom. You've got an assessment that's 100% checked and scratched, scored automatically of. Um, course using the beautiful power of AI, but also, um, you know, coding, SQL data, Excel, Google sheets, etc, um, to know it's easier than ever. So they're looking to digitalize, let's say the home assignments that might be floating around the ulcer, you know, now in 2026, it's easier than ever to use a little bit of external help that you may not want the candidate to do. So it's also about how can we give the candidate the free freedom to do this test in their own space, in their own time. At the same time, how can we rely on the results of the test? And of course we have huge suite of cheating prevention tools. Copy paste detection, tab switching detection, IP address tracking, webcam snapshots, question randomization, a whole bunch of things at the same time. And also now more than ever, the, the conversation of AI. At first it was like, people can't use AI. I want to stop people from using AI. And then it was, I don't mind if they're using AI, I just want to see how they're using AI. And, and now it's evolved to I must see how they're using AI. I need to see how they can prompt. I need to make sure they can do vibe coding and data sets and use, you know, their judgment, sound judgment, like finding that nice balance between machine and human. And so we have.

Speaker B: Right.

Speaker A: Huge AI library for that. Um, and um, yeah, it's really just uh, it's just again, it always comes back to really making the assessment is realistic as the challenges of the role for the best predictor feature job performance.

Speaker B: So two things, one or two last things. One is, um, when you look at your feature set, what do you wish your customers would use more?

Speaker A: Oh, can I say two things, Myla?

Speaker B: Yeah, two lines of thought. No, you say two things. You say three things if you want.

Speaker A: So again, like, I, I feel like everyone is, uh, is, is over, over the buzzword of AI. But we have some really, really cool, like I'm, I'm going to say disruptive, uh, features. Um, number one is the embedded ChatGPT. So it's an embedded monitored ChatGPT. It means that for some assessments and our users can choose this one yes, this one no. They can allow candidates to use it. They can see everything. They can see what their prompt, their answer, how they use it, what their thought process is. And there's always different levels, right? Some people are using AI to polish an email. Some people are using AI to build workflows. Some people are training 10 agents at the same time. Some people are doing 15 hours of work in one hour. And so it really depends on what level you're looking at, where you are as a business. And it's also really important because every business is using AI and has their internal policies about what is and what's not being used AI. So there's no one size fits all. And I would say it's genuinely a very like, it's a, it's a pleasure and also a challenge to really get into the mindset and say, okay, what are we really trying to evaluate? What are we like just take a little like further deep into the jd like really tell me like what's the most important thing when someone's coming in through this uh, hiring process. Another thing is uh, AI auto scoring over open text and video. So this has also been a really, really huge release that we did, um, recently. I would say people use it, people use it a lot, but we have like pre built agents, things like language comprehension, um, that's compatible with every language. We have pre built agents for things like conflict resolution. So you said earlier I want to see how they handle, you know, the frustrated customers. A lot of people do. They can just pop that on and it's going to evaluate empathy. Did they, were they polite, did they stick to the facts, etc. But a level on top of that is our custom agent. So our clients can also set custom scorecard agents. Did the candidate mention A, did the candidate mention B? Was the answer over this? This is like the basic, basic line. Some of our clients and also our team are able to support our clients building very sophisticated prompts. And when AI is set in the right way, it means that every single candidate gets the same questions, the same answers with the same scorecard. Doesn't matter if it's Monday morning, Friday afternoon, it doesn't matter. The AI also doesn't know how the candidate in their telephone screen, the AI doesn't know how they answered, uh, in the rest of the test. And so when it's set up properly, and this is absolutely imperative, it is the only way that we can ensure the unconscious bias does not creep in. And it's the unconscious bias. Right. We don't even know that we're aware that we're doing it. Those are two absolute showstopper features that uh, um, I love when our clients come and really utilize them to the best of the, to the. Yeah, the best of the ability.

Speaker B: So what's your title again?

Speaker A: I'm the head of Customer Success.

Speaker B: So how do you define that?

Speaker A: Oh, how do I define that?

Speaker B: What? You just wanted me right there. What?

Speaker A: Uh, I'd say my job is really to ensure that I understand what our users are looking for. You know, uh, I understand the use case, the most important use case, but not just what they're looking for today, what they're looking for in three months, six months, what they're looking for in a year. Um, my job is to make sure that they understand the most relevant features because we're doing lots of things from pre screening chatbots available on WhatsApp, uh, video interviews all the way to, you know, simulations for AI engineers and so on and so forth and everything in between. So it's really to make sure that the prospect is aware of the most relevant M parts of our product for their role is to support them in questions, implementation, training, onboarding. And it's the uh, you know, the support and um, you know, the professional services that we give is not just at the beginning, it's all the way throughout. And it's something we're, we're really, really, really, uh, put a lot of emphasis in and really thank goodness we, most of our clients have been with us for years and years and years and as I say, as years go on, we're able to really optimize everything and bring it back and get better and better and better. Um, so we really start to understand the niche, etc. So that's my job, is to really make sure that the customers have success. As cheesy as that sounds, you know,

Speaker B: drop smile, walks off stage. Ellie, thank you so much for your time.

Speaker A: Thank you so much. It was great.

Speaker B: It's been wonderful and thanks for the audience for listening and watching. Until next time.