People on LinkedIn aren’t looking for a job and too many candidates on job boards aren’t qualified. Therein lies the heart of start-up Uncommon.co and how it hopes to break through the crowded space of recruitment technology.
The company says it uses AI technology trained on over 50 million career paths and analyzes applicant resumes for hard skills, like expertise in data science or kinesiology, by looking for factors like degrees attained or years in a role; soft skills, like creativity and entrepreneurship, are found by extrapolating skills necessary for success in past jobs.
Chad & Cheese put Teg Grenager, CEO, through the gauntlet and see if his company has what it takes to make it in the world of recruiting. The companies that put $18 million in their company recently certainly hope so.
And after listening, be sure to checkout Jobs2Careers, exclusive sponsor of the show. Jobs 2 Awesome, more like it!
Chad: Okay Joel. Before we get into Firing Squad, I have one quick question.
Chad: Would you say that most companies find it hard to attract the right candidates to apply for their jobs?
Joel: Well, Jobs2Careers certainly thought so. That's why they created their new talent attraction platform, ODT. Yeah, you know me.
Chad: Dude. That's OPP. This is ODT. Which stands for On Demand Talent. Where data driven talent attraction is made easy. The On Demand Talent platform enables recruiters to reach the right talent at the right time at the right price.
Joel: And the best part?
Joel: You only pay for what Jobs2Careers delivers.
Joel: So, if you're attracting the wrong candidates, or you feel like you're on a recruiting hamster wheel, just go to Go.J2C.com/CC and learn how On Demand Talent or ODT, yeah you know me, can get you better candidates for less money.
Chad: Whoo! I'd say you just go to ChadCheese.com, click on the Jobs2Careers logo there and it's just that simple.
Joel: It is simple. Arm me with Harmony.
Announcer: Like Shark Tank? Then you'll love Firing Squad. Chad Sowash and Joel Cheesman are here to put the recruiting industry's bravest, ballsiest and baddest start-ups through the gauntlet to see if they've got what it takes to make it out alive. Dig a foxhole and duck for cover kids. The Chad and Cheese podcast is taking it to a whole other level.
Joel: Alright, alright, alright. What's up everybody? Joel Cheesman here. Chad Sowash up on the other line. And welcome to Firing Squad.
Chad: Here we are.
Joel: Today, we have a very special guest. We have Teg Grenager, I believe I pronounced that last name correctly.
Chad: Butchered it.
Joel: Teg is with Uncommon.co. Utilizing a lot of AI automation, cool stuff. He's going to tell us more about it. And Chad and I are going to determine whether or not he is going to pass the Firing Squad without injury. Chad, how are you doing man?
Chad: My trigger finger is itchy dude.
Joel: I know. We talked about that. And I'm a little drunk still from Ireland. So the guns could go off today, I don't know.
Chad: Well excellent. So Teg. So what's your position there at Uncommon.co? You chief bottle washer? What's going on.
Joel: Quick intro.
Teg: Yeah, I am chief bottle washer. But I'm also chief executive officer.
Joel: Very nice. Very nice.
Chad: So, here's how it's going to go, my friend. You will have a two minute pitch. And at the end of two minutes, you'll hear the bell. Then Joel and I are going to hit you with some rapid Q&A. Now if your answers aren't concise, Joel is either going to hit you with a bell or the crickets, whatever he feels like he wants to hit you with.
Joel: I prefer the crickets, because I'm natural like that.
Chad: But they generally put him to sleep.
Chad: At the end of Q&A ... we've got a three point scoring system here my friend. You will either receive big applause, which means you exceeded expectations. The golf clap. My favorite. You're on your way, but you have a good amount of work to do. And then last but not least, you don't want to be in front of the firing squad.
Chad: That pretty much means-
Chad: That pretty much means you're going to pack your shit up and go home. But that's it. That's the firing squad. You're going to hear the bell. You're going to start the pitch.
Joel, it's on you man.
Joel: Teg, are you ready?
Teg: I am totally ready.
Joel: Two minutes starts now.
Teg: Alright. Thank you guys so much for having us on. So I want to tell you about Uncommon. Uncommon is a programmatic talent marketplace that makes it really easy for recruiters and hiring managers to use and benefit from programmatic recruiting technology. But no mistake, this is not a job advertising system. This is not complicated. Uncommon doesn't require any training. It's designed to be simple and intuitive for everyone to use.
Teg: With Uncommon, recruiters can imagine the perfect candidate for their position, write down the precise qualifications that meet or exceed the, sorry, the precise qualifications that they should have and then sit back and receive a stream of applicants, interested applicants that meet or exceed those qualifications. It's very simple. And we think it's the way things should be.
Teg: So put yourselves in the shoes of a recruiter who needs to source candidates. I know we've all been there. And today you have two choices. One, you can advertise the job on a bunch of job boards, in which case you have to, first of all, figure out which ones to advertise on. Then you have to pay them usually on a CPC basis and when you sit back, you get a flood of candidates who are very interested in your position, but mostly unqualified as well. And then you have to spend your time screening them to figure out who are good ones.
Teg: Or number two, you can go license an expensive database of passive candidates and write down some complicated boolean search string, in which case you get a bunch of candidates who are very qualified for your position, but not interested. So you have to spend your time of course trying to convince them that they need a new job in the first place and that they should be interested in your job at your company.
Teg: So we at Uncommon are changing all that. We provide recruiters with a stream of candidates who are both interested and qualified out of the gate. And we show you, this is my favorite part, in a side by side comparison exactly how each of those candidates stacks up against the required qualifications that you asked for. It's like a dream come true. And best of all, Uncommon has introduced a new pricing model. We charge the employers on a cost per interested and qualified applicant basis. In other words, you only pay for the interested candidates that meet or exceed those custom qualifications that you wrote down initially. This means that we're totally aligned with the recruiter's best interest.
Teg: Make sense?
Joel: Makes sense. Are you done?
Teg: Awesome. We're transforming the in ... okay.
Joel: Uncommon.co. I'll tell everybody for you. Okay.
Chad: Uncommon.co. Yeah, no, good call man. You got two minutes. I think we're giving them way too much time. Because they're just killing us.
Teg: A little nervous.
Joel: A little nervous here, I think.
Chad: I love it. He's listened to the Firing Squad before.
Teg: I don't know why, with that firing squad out there in front of me.
Chad: So, where the hell are you finding qualified candidates? You're going out from a programmatic standpoint, pushing jobs out. And how does that work from there? Just for the talent acquisition, VP or Director or Manager, whatever, who's listening right now, how does that actually work for me?
Teg: So I don't want to focus on it too much when I talk to recruiters, but of course, we do have AI and data science at the core of everything we do. That's my background, you guys might know already. So the last company that I built together with our founder, Amir Ashkenazi, was an advertising marketplace, a programmatic advertising marketplace. And we heavily leveraged AI and machine learning there as well. So we basically are using those technologies to do the things that recruiters would have to do themselves if we weren't around. And that they have to do today without Uncommon. So we figure out which job boards to post on, we figure out as the candidates come in, as the applicants come in, which ones are actually meeting the requirements and why. Show you side by side.
Teg: And we also go to other source of candidates. We have increasingly our own growing database of candidates as you can imagine. People that we're looping in and engaging over time. So we reach out to them and ask if they're interested, the ones that are qualified. And we hit third party passive databases as well.
Teg: But the whole point is that the recruiter shouldn't have to know about all that. That's like mechanical stuff that machines can be really good at. The recruiter should just focus on what kind of candidate they want to talk to and then let us know about that and we should do all that hard work for them, whether it's looking at passive databases or screening through the active ones, whatever it is.
Chad: So, it sounds a lot like Zip Recruiter. How do you differentiate yourself from Zip Recruiter?
Teg: Good point. Zip Recruiter is a great company. And I think they've obviously experienced tremendous success and growth recently. There are some really big differences. First of all, Zip Recruiter doesn't ask you in a precise way what kind of candidates you want to look for. So when you sign up with Zip Recruiter, you specify, you list the job they are looking for and you write some text in your job description, but you don't actually tell them who you would consider to be qualified. And so when they send you candidates, it's generally everybody. They sort them for you, but they generally are sending you all stripes of candidates. People that you consider qualified and lots of people that you don't.
Teg: Second of all, I think Zip Recruiter has really focused, and I think these two are actually related. I think Zip Recruiter is really focused historically on the small and medium sized market. They've generally been serving small mom and pop and other kind of local businesses with lower skilled jobs. And we're really, we serve those guys, of course, but we're really focused on skilled jobs. And we've built a system that's filled with pretty sophisticated models of skills and experience in different kinds of roles and different kinds of companies and all that kind of stuff. And that's just stuff that Zip Recruiter hasn't done yet, mostly because they haven't really had to, for the kind of customers that they've been serving.
Chad: So, you're mainly enterprise, is what I'm hearing then?
Teg: Yes. I would say that we are currently, our customers are largely, are mostly kind of large enterprise, although we also work with many staffing agencies as well. But yeah, typically I think we do best on those high skill jobs that are at a range of verticals, but still where there's really a heavy screening task that otherwise a human would have to do.
Joel: Hey Teg. I'm going to go the other direction from Zip Recruiter and I have the luxury of doing a report on you guys. We've talked previously. And I think there's a serious Intello kind of component, where you guys have 50 million, or at least when we spoke, there were 50 million or so profiles, I believe.
Joel: How are you different from an Intello, a Hiring Solved, from that side of the product?
Teg: I think I lost you for a minute, but I think you're asking how we're similar or different from Intello, Hiring Solved, Job Jet, those kind of guys, right?
Teg: Yeah. So in my opinion, they're solving part of the problem. But they're focused so heavily on finding passive candidates in these big databases. And they're not activating those candidates for you. They may give you some tools and maybe you guys know differently, maybe there are some who are doing a great job with this, but what I've seen is that you then get an opportunity to reach out to these people, but it's still left to the recruiter to try to go and turn them into interested applicants, from ... they may be qualified. It's easy to find qualified people in those databases, but there's still a lot of work to be done. You've got to reach out to them, often to have some kind of pipeline or some kind of ... increasingly we're talking about CRM for job seekers and so on. And we believe that, again, recruiters shouldn't have to do all that. That's something that we should do. And that we can go and leverage those databases and we have partnerships with databases that are similar to some of the guys you mentioned. But all that work of trying to engage those candidates, that's something that we're doing for the recruiter and the hiring manager.
Chad: So there's a marketing aspect that a Brilent or Hiring Solved or what have you, does not have that you're saying that Uncommon does.
Teg: Exactly. So to come back to my pitch at the beginning, the candidates have to be interested and qualified. What does every recruiter want? They want a list of interested and qualified candidates. In other words, people that have already said they're interested in the job and they know meet the basic qualifications, that they're ready to then show to their hiring manager. And if you're going to go use a big database, you're going to have to go turn all those qualified candidates into interested ones, get them to actually apply, indicate their interest. Or the other way around, if you're going to go and collect all the stuff coming in from job boards, you're going to have to take all these interested people and figure out who's qualified.
Teg: So again, we think that that's something that is very automatable. And we provide a beautiful system that allows recruiters to do just that in an automated way.
Joel: So, there's some big companies getting into the AI space, as you well know. A little company named Google. Do you guys think that you can out AI Google, knowing that they've turned their guns on the recruiting space?
Teg: Oh, I love that question. So, for reference, in my last company, AdaptTV ... it was a video ... we were building a video ad, programmatic video ad marketplace. And Google had just bought two amazing companies when we started our company. They had just bought YouTube, which meant that they were basically the king of online video. And they had just bought Double Click, which those of you may remember, was the premier largest ad marketplace. And we just thought, okay. This is it. They're going to eat our lunch. Why are we even doing this?
Teg: And it turned out that Google moves very steadily. They're very smart. They move very steadily, but they also move very slowly. And typically, predictably. And they do things in a very Googly way. And over the years that we build AdaptTV, we actually ended up partnering with them a lot more than competing with them. And they didn't in the end, I think, have a negative impact on our success.
Teg: Now who knows what's going to happen here? I can't know what's going to happen in the future, but I see the moves that Google is making, just like you do. I have a very similar view on it. I think that they are disintermediating essentially the big job search engines. I don't need to name them, but you can name them.
Joel: And we do weekly.
Teg: And that that is a landscape that we're now going to have to live in. Unfortunately with our strategy at the moment, this is honestly at the moment, just kind of lucky, but we're not going head on for them. That we can benefit from a world where Google does a great job with job search, because we work for the employer typically. We sit between the employer and the job seeker and help make that application and screening process great. And we can keep doing that, because the employer wants to keep doing that, even if Google is the one that's providing job search.
Joel: Teg. I'm really curious about your pricing model. I believe you call it Pay per interested candidate. Is that correct?
Teg: Hey. Thank you.
Joel: Yeah, tell us about that. Expand on that for a minute.
Teg: Yeah. So cost per interested and qualified. We invented that term. What we've seen so far is that the world is generally operating on a CPC basis, and that's itself sort of an innovation over the old listing fees that we've had for the last decade or two. But we think CPC is wrong. And the reason why CPC is wrong, it's wrong for the customer. It's wrong for the recruiter. Because when the large job boards are billing you CPC, their incentive, their motivation, of course, is to send you more clicks. And more clicks doesn't mean more qualified clicks. So, yeah, exactly.
Teg: So, you know, so what we see is that, that actually it's a sad thing, because if you think about the way job matching has worked forever, it typically starts with an employer listing a job and an applicant indicating their interest. It doesn't have to be, but that's historically how it's been for most of history. And basically, employers have lost faith in the job boards. They've lost faith in that active candidate channel because the quality has gotten so low. So we don't believe that has to be the case. We actually see a lot of good candidates coming through the active channel. But they need to be, there needs to be a level of automatic qualification put inbetween so that that employer is not just overloaded with these people who are spraying and praying for their job search.
Joel: And is this different than cost per acquisition? Just to be clear.
Teg: I think that it is, very much. Because it's cost per qualified applicant, right. So it's, or cost to acquire someone qualified. So we're running the automatic screening with a side by side comparison. We're doing that for every candidate. What's really cool guys is that it can benefit not just the employer, it can actually benefit the job seeker. And we're already doing a little bit of this and we hope to do a lot more of it in the future. But we can actually show the job seeker as they're coming in, as they're indicating interest in the job, as they're applying for the job and so on. We can show them where they stand. And not in some kind of fuzzy way, like you're in the top 10% of candidates for this position, which you can see on certain, like LinkedIn and so on, but that's always been nebulous to me. Well, what does that mean? Am I going to get a call back or not? Am I qualified or not?
Teg: We actually can tell you, show you the same side by side thing that we show to the employer. We can show you, hey, here's where you stand relative to the things that this employer, this hiring manager has said is important to them. Wouldn't you love to know? Right. And if you can see that you're clearly falling short, there's things that you can do. Maybe you forgot to put stuff in your profile on your resume. Or maybe you want to go back and get a little training. Right.
Teg: I've been talking to a lot of people recently who are taking courses that, like general assembly, or boot camps or online courses. And these things can really help people backfill missing positions, if they have a particular job that they're going for. And we're, our service, because we're automating and creating this transparent and automated view of the qualification of the candidate for the position, we actually have the power to be able to do that and to help the job seeker in that way. And I don't see anyone else right now who can do that.
Chad: So on the CPIQ side of the house, you're talking about interested. Well, yeah, they applied, so therefore they're interested. So you check that box. And qualified, you pretty much have an arrangement with the employer. Let's say, hey look. These are your requirements. If they meet these requirements, than they are qualified. So therefore, that's when you go in and that's when we bill you for that candidate. Is that how it works?
Teg: So, yeah. Very good. Thank you for asking me to qualify Chad. That's exactly right. Joel saw a demo of it earlier. And I wish I could demo on the air, but of course that doesn't work so well on a podcast. But yeah, basically you know, there are other pricing models you can imagine. Like obviously, you can go all the way to the hire and have a success fee and then you look like a contingency agency or whatever. But we're trying to find a happy medium of something that we can do really well. Like a metric that we can optimize to. Or a goal that our system can be trained to optimize to. That is also total aligned in the interest of the employer.
Teg: And so we have found that what works really well for us is that when the employer is rigorous and writes down what they're looking for and that's part of our process. It does take an extra minute up front. We got to ... instead of just writing a job description and copying and pasting a bunch of requirements, you've got to actually think and write down the requirements you're looking for. And once you've done that, when we find people that meet them, that's when you pay. You pay $9.95 by the way, just to be very clear. That's our introductory pricing. We can actually have a whole cool discussion about the future of pricing. I believe that in general, it should actually be dynamic, not static. But we're starting to keep things really simple with a $9.95 per interested and qualified candidates. This is the one you've talked to and who meets all of your custom requirements.
Teg: But that means that you do have to think in the beginning, what do, ... sort of visioning your future. Like, you need to sit down or think, what is it that I want to, who do I want to talk to? What do want to receive? Before you start the process. Because then you are going to pay, yes.
Chad: So on the partner side, following up. You were talking about Google. So how specifically, and I see it on Uncommon.co, you're partnering with two big names. Google and Amazon. How are you partnering with them.
Teg: So I believe that they're actually listed as customers on our website, not as partners for right now, just to be super clear. But actually to talk about today, how we are. So Amazon ... hey, wait, wait, wait. Why?
Chad: He was giving it to me.
Teg: Oh. Okay. Alright. Well, Bill wants to make sure the website is clear. But.
Joel: No Chad.
Chad: The website ... wait. First off. The website says Joel, dumbass, Brands we've proudly partnered with.
Teg: Oh. You're right.
Chad: I know I'm right.
Joel: Chad is rarely right, for the record.
Teg: Alright. These are our customers. Okay. Just to be clear. Everyone knows they are our customers.
Chad: Well you've got some pretty big name customers. But you did say earlier that with an earlier venture, you partnered with Google. Are you partnering with big companies now? Like the Google's and the Amazon's.
Joel: Google for jobs.
Chad: To be able to fill out your product offer.
Teg: Okay, so the answer is yes. I don't have any to announce. But you guys would be, definitely on the short list if we, if and when we have some cool announcements to share. But let me give ... well, there's a very obvious way to work with Google right now, which is that we are building a product that is starting on the recruiter side, the employer side. And so we're very happy to have all of our customers position listed on Google. And we're actually getting nice, healthy, you can call it SEO or whatever you want to call it, but a nice flow of candidates from Google for jobs. So that works very well for us.
Teg: But if you want to think just more generic terms about some of the, let's say incumbent job boards from the decade past, there is a great opportunity without naming any names for us to white label or otherwise provide technology to them so that they can start to operate, instead of on a CPC, they can start to test out this new CPIQ model, on both sides potentially, with their job seekers and with their employer relationships. And the reason why they might want to do that is that they see that, they see the writing on the wall like we do, that Google is going to really eat up a big part of their value proposition and that the old CPC model for just getting search clicks isn't going to sustain them forever. So they're quite interested in exploring partnerships with innovative technology companies like ourselves.
Teg: And by the way, for any of those people who are out there listening, we do have some very cool partnership opportunities, if you are a job board or a job site. We can take the very sophisticated and I think very innovative technology that we have inside and white label it and make it available for people to create their own offerings. And that's something that we're very happy about.
Joel: Always be selling Teg. Always be selling.
Chad: Always be closing.
Joel: Yeah, that too. Chad and I have been around quite a while in this industry. And the companies that kind of come and go are typically ones where there's very little core competency or experience in the employment space. And if I'm incorrect let me know, but it sounds like you guys are from a totally different world than recruitment. So what do you think, if that's the case, is that an advantage, a disadvantage? Talk about that.
Teg: Well, first I want to say it's an advantage. But I also want to have enough humility to say that I hear you. And there's a lot that I don't know and I'm learning every day. So yeah, I'm definitely coming from outside of recruiting. I never worked at a job board or an ATS. And every day is about learning for me in our company. We do, or course, have a lot of people now working for us who bring some pretty deep experience in our industry.
Teg: So for example, our significant people in our data science team have actually come from recruiting other, very exciting, out of recruiting tech companies of days past. But you know, so I'll tell you the advantages. So the disadvantage is I have to learn everything and every day is a new day. The advantage is that there is actually a tremendous amount of experience that I think we can bring from our experience, our time in online advertising.
Teg: So online advertising went through a programmatic revolution while we were building and running AdaptTV. And basically when we started, there was no such thing as programmatic. And by the end, programmatic was the lion's share of the digital spend. People decided that it made a lot more sense to spend their money with data, actually cherry picking. Understanding who the audience was and the users were and cherry picking and advertising to the people who actually were interested in their products. And they found that that created a lot of value. And of course, needed a lot of technology. It needed to be able to represent this huge datasets of users. And you needed to be able to make decisions very quickly in an automated way. But we built all that stuff over several years. And that was incredibly rewarding and created a lot of value.
Teg: And I think recruiting is going through the same thing now. It's just the very early days. But we are, employers can benefit tremendously. And I don't have to tell you guys this, but from more deeply understanding ... I mean, imagine putting an ad out there and having no idea who you were showing it to. That would be silly. That's like 200 year old advertising technology.
Teg: But it's the same thing. Recruiting today is listing job ... job boards are showing jobs to candidates where they have no idea whether that candidate is qualified for that job, is interested in that job. It doesn't make sense. Instead, we have tons of data about these candidates. Let's use it as they come in and let's use it to show them the right jobs and to then show the right candidates to the employers. It just makes sense.
Chad: So on the other side, you guys actually state that you leverage, are transparent and objective analysis of qualifications to increase diversity and reduce bias. How does your system? Because you have all this data. And this is about, obviously, how you're dealing on the recruiter side of things. How do you boost diversity?
Teg: I love this question, because it is one of the reasons that I think many of us in the company get up and come to work everyday. If you think about how recruiters and hiring managers make decisions today, it's very manual. Typically it involves reading or reviewing a whole lot of resumes and profiles. And we've all been there. It's very hard to make those decisions. You're going to spend maybe 30 seconds, maybe a few minutes looking at a resume. If its really interesting. And you're trying to make that ... it feel like a gut decision, for a lot of us, when we're doing it manually. It's sort of like, yeah, this guy doesn't really have what I ask for, but on the other hand, why I really like that company or that school that he worked at. And wow, that project sounds really, that's something, I worked on something like that. Or I understand people like this, or whatever it is.
Teg: And we're using gut, we're doing gut decision making basically. And we all know that that can be very good, productive in certain domains, but also does of course, it's filled with implicit bias. Even if we're trying not to be biased, we are. And so, by giving some of those early decisions about the level of qualifications of a candidate over to a machine, who's going to rigorously just follow, do the most dry and boring comparison, cut and dried comparison possible, we do remove that really big factor, that introduces bias at the beginning of the process.
Teg: Now we can't remove bias from all process, of course not. But we can at least have a positive impact in that screening process. So that's one of the things that, one of the benefits, I think that we provide, over and above obviously, being cheaper, faster.
Chad: So, you're really removing the face of the candidate, per se, and just trying to boil it down to, do they meet the qualifications. The big question is, and this is the hard part. And I think this is what you actually talked into was, what if the requirements are actually biased themselves?
Teg: Yeah. No, that's a real, well ... one of the fun things about being in the position we're in, is that we are defining the language that employers and candidates are using. We're asking our customers and it's mostly coming from them, but we also get some editorial say. And like, what kind of requirements do we put in there? So, for example ... and we've been very judicious about choosing the kinds of requirements, or even able to put into the system today. So I don't have an age requirement, for example, because our nationality requirement or obviously a gender requirement. You can't put those things in as requirements. And I've had people really ask me for age over and over again. And we have not done it. And the reason is, I myself am 46 years old. So I'm getting up in the years. And if I wanted to go get a software engineer position or any other kind of contributor position, I'd have a lot of hiring managers who'd start to look at me and say, "Well, he's kind of an old guy. I'm not sure I really want to hire him."
Teg: And so I've had a lot of hiring managers come to me and say, "Hey can I put a limit, like an upper limit on the years of experience or the level of seniority?" And that in general, we have not done. We do of course have a lower limit on years of experience and level of seniority, but the upper limit I think is prone to be abused. And we can handle ... and I'm like, "Why? Why do you want to not hire someone more senior? Like, wouldn't they be more experienced?" And then you dig into it, and they're like, "Well, I'm afraid, because they're so senior that they won't like the job or that their salary expectations are going to be too high, or whatever. And so, we're going to try to address those things separately, in a more specific way, but not just like, Hey, let's discriminate against people that have a lot of years of experience."
Teg: So that's just one that I happened to relate to, but obviously we're doing the same thing across the line with a cultural and ethnic background and sexual orientation and gender and all this kind of stuff. So we keep those things out of the qualifications. And we keep the qualifications really cut and dry.
Joel: I'm sorry. I've got to pull the plug on this diversity stuff and compliance. Chad loves it. I've had enough.
Chad: Everybody loves it but Joel.
Joel: Yeah. Teg, last question from me. You guys have recently raised a lot of money. Tell us about that. And then, tell us what are you planning on doing with the fundage?
Teg: Well, so we raised $18 million, a series A, from three different investors actually. So we have-
Teg: Yeah. We have Spark Capital, we have Kaden Partners and we also have Ventures. So some of these guys actually invested in our last companies, so they're folks we've had a good relationship and a long time. We're not going to do anything mysterious with that money. It's very simple. We're going to continue to develop our product and to market our product. So, both of those things cost money. We have an incredible engineering and data science team I'm super proud of. So we're going to continue to fund them and grow that team. And then of course, we're going to invest in sales. And you guys know about that as well, but you've got to get in front of all these recruiters, especially in the enterprise and the large agency, staffing agency space. We've got to have people to help connect to those agencies. So that's another area of our investment.
Joel: How refreshing that you said sales people.
Teg: I didn't actually say the word sales people. But yes, we're employing sales people.
Joel: Alright. Chad, I'm ready to send my card in. How about you?
Chad: I am.
Joel: I'll go first, if that's okay.