The RUSSIANS are coming!! We were totally unprepared for this chatbot startup. Mostly, because of the mere fact that they're so far off the radar. They sound more like a Marvel villain.
Boy, we did not see the Firing Squad that unfolded coming. How'd it go?
Gotta listen to this Talroo exclusive.
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Chad: Hey, Joel.
Joel: What up?
Chad: Would you say that companies find it hard to attract the right candidates to apply for their jobs?
Joel: Well, Jobs2Careers thought so.
Chad: Jobs2Careers? You mean Talroo.
Chad: Yeah, Talroo. T-A-L-R-O-O.
Joel: What is that, like a cross between talent and a kangaroo?
Chad: No. It's a cross between talent and recruiting.
Chad: Talroo is focused on predicting, optimizing, and delivering talent directly to your email or ATS.
Joel: Ah, okay, so it's totally data driven talent attraction, which means the Talroo platform enables recruiters to reach the right talent at the right time and at the right price.
Chad: Okay, so that was weirdly intuitive, but yes. Guess what the best part is?
Joel: Let me take a shot here. You only pay for the candidates Talroo delivers.
Chad: Holy shit. Okay, so you've heard this before. So if you're out there listening in podcast land and you are attracting the wrong candidates, and we know you are.
Joel: Mm-hmm (affirmative).
Chad: Or you feel like you're in a recruiting hamster wheel and there's just no where to go, you can go to Talroo.com/attract. Again, that's Talroo.com/attract and learn how Talroo can get you better candidates for less cash.
Joel: Or just go to chadcheese.com and click on the Talroo logo. I'm all about the
Chad: You are a simple man.
Thad: Yes, my precious, yes. My most precious candidates sweet, precious, yes.
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 startups 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.
Chad: There it is.
Joel: It's been too long since we've had a Firing Squad.
Joel: Hey everybody, this is Cheese and that guy, whatever, is Chad. Our special guest today, special startup today is XOR.AI.
Joel: We'll get to the name in a second, but representing XOR is their CEO and
founder, Aida Fazylova. Aida, how are you?
Aida: I'm good, thank you.
Joel: Good. Love that you're here. Give our audience a quick elevator pitch on you and then we'll get to the rules and then get to your company.
Aida: Yeah, sure. My name is Aida, I'm founder of XOR. Prior to founding XOR, I've been working in IT recruitment for six years, and the company was born out of by personal pain.
Joel: That's good.
Aida: What frustrated me was working as a recruiter was that 60% of my working hours I was spending doing routine and repeated tasks like prescreening the resumes, scheduling the interviews, so this is why I found a co-founder two years ago and we founded this company.
Joel: Aida is Russian if you couldn't tell from the accent but lives in Austin, Texas, which I think is very cool.
Chad: Yeah. Our first Russian.
Joel: Our first Russian, yes. We're very international on the Firing Squad. Chad, read her the rules and we'll get to XOR.
Chad: Okay, Aida. You will have two minutes to pitch XOR.ai. At the end of two minutes, you will hear the bell, then Joel and I will hit you up with rapid fire Q&A. If your answers aren't concise enough, Joel is either gonna hit you with the bell or crickets, which means you need to tighten up your game, quit being so long in the-
Joel: Move it on.
Chad: Yeah, keep it moving on. At the end of Q&A, you're gonna receive one of three, big applause.
Joel: Oh, you'd go with that one first. It's the last one on the sound board.
Chad: Which means you've exceeded expectations and you're kicking ass, taking names, or we believe you're going to. A golf clap, you're on your way but you do have a lot of work to do, or last but not least, the firing squad.
Chad: Which means it's probably time to pack your shit up and go home. So that's the Firing Squad. It's time to carve up your jack-o-lantern and show it to the judges. Okay, Joel, are you ready to-
Joel: Halloween reference, I like that.
Chad: You like that? Are you ready to start that pitch timer?
Joel: I think Aida's still here. Okay Aida, you've got two minutes starting.
Aida: Yeah. So at XOR, we help employees to accelerate and streamline their recruiting efforts using chatbots and AI, so we automate the initial candidate engagement, prescreening, scheduling, answering frequently asked questions, and work with cold candidate database from your ATS. The implementation of our customers experience three main things, first one is decreasing the time to hire by third, decreasing the cost per hire by half, and significant improvement in candidate experience and increasing the conversion rate from visit to apply by 85%.
Aida: So we've been in the market for two years now. So far we've processed over two million candidates. Right now we work with 121 corporate customers in 15 countries, both direct employees and staffing agencies. We are at 1.6 million dollars ARR right now. And yeah, that's about it.
Aida: Also, a thing about XOR is we recently made a survey for randomly picked candidates asking them how did you like the experience with a chatbot, 93.3% of them said it was excellent experience, 6% said it was good, and less than 1% didn't like it.
Aida: So the company is headquartered in Austin, Texas. We keep the development team in Moldova, it's in Eastern Europe. I'm originally Russian, as you said, so yeah. Main differentiators in the market of XOR from everybody else is first one is we support 103 languages while everybody else supports a couple of them for the most part. Second one is we have the richest feature set that lets us cover the most retained repeated tasks from the moment the candidate is curious up to the moment of the job offer. Third one is we are the most enterprise ready, that means GDPR compliance, technical compliance, and really domain expresses that lets us do the very smooth change management within the customers.
Aida: So far very high customer satisfaction, we have zero turn rates for two years. Yeah, that's about it I think.
Joel: Your time is up. For those who want to find out more about XOR, where would they go?
Aida: It's XOR.ai. X-O-R dot A-I.
Chad: So right out of the gate, the name. Where did the name come from?
Aida: The name stands for extraordinary optimized recruitment, and we do know that people call their chatbots with a female name.
Joel: Whoa, whoa, whoa, time out. Say that again?
Aida: It stands for extraordinary optimized recruitment.
Chad: Extraordinary recruitment. Okay. So it has nothing ... you're a mathematician right?
Chad: It has nothing to do with XOR gate at all?
Aida: It does. It actually started as binary operator. Then we found a way to kind of decipher it for the recruitment purposes.
Chad: So you started with the whole mathematician side of the house, the XOR gate piece and then you went mainstream and sold your people out, sold your mathematician people out. I have to give you big applause for that one, good one.
Joel: Logistically though, isn't Xor a difficult time for your sales folks? Like I can't imagine calling up an HR professional and saying, "Hi, I'm Johnny with Xor." How do they get around that? How do you spell that? Is that an issue right now with the company?
Aida: Not an issue at all. Absolutely not.
Joel: Okay. Have you guys gotten funding at this point?
Aida: The company ... we started from Eastern Europe. You know what situation this is right now is there, so the company has been profitable from day one. We've been bootstrapping for a while with my co-founder. Then we started to make money and then we started to hire people, but we got the angel investment from two Austin based angels of $350,000 in the beginning of this year. One of them actually joined us as a COO. It's a person who exited his previous company for $1.2 billion to Emerson. His name is Dave Perry.
Aida: He's based in Austin. Yes, he's our COO right now.
Joel: I just want to get this straight real quick, because your pitch was a little bit quick for me. You're $6 million a year in profitability or revenue?
Aida: We are 1.6, 1.6 in ARR.
Joel: One point six. Okay.
Aida: Regarding revenue.
Joel: So the only money you've taken is $350,000.
Aida: That's right.
Joel: And you have how many employees?
Aida: Twenty five.
Joel: Twenty five. You have 121 customers.
Joel: And you've been around for two years.
Aida: Yeah, we started the company a little bit more than two years ago, we've been in the market for 18 months, 18 to 19 months.
Joel: I like everything you just said there, by the way. Okay. Chad, you're up.
Chad: A little bit more background. You started in IT recruitment and you said there are three things that you wanted to be able to change that you had pain around. What were those three things again?
Aida: Absolutely. As a recruiter, I'd been spending, as I said, 60% to 50% of my working hours doing three things, first one is prescreening the resumes, second one is scheduling and rescheduling interviews which killed me. Everybody hates to do this. Our third one is answering the same questions over and over again, like you know, will you provide me with Visa support? Can I bring my cat to office? And so on and so forth, so I had to find a way to automate that without losing the human kind of touch for the candidates.
Chad: Can I bring my cat to work? I like it.
Joel: I bring mine to work.
Chad: We know.
Aida: Even though people do know for sure that it's not a human at the other end of the thing, it's a chatbot, they're getting so engaged that they always ask all types of personal questions, like are you a robot? Do you have a girlfriend? What's the weather in London, and so on and so forth, so it's really, really hilarious. That's why we added the small talk functionality with the chatbot and now it can handle all of those questions. That's pretty cool.
Chad: That's hilarious. Where did everything actually start? Where was your first customer? Where location wise and what was the customer's name? Talk to us about that story.
Aida: Absolutely. Our first customer was the largest retailer in Eastern Europe, it's called X5 Retails ... X5 Retail. They have three retail grocery chain stores, chains back in Eastern Europe, so altogether they have 200,000 employees and they use XOR in order to stay in touch with their candidates after hours, during the weekends, during the holidays, and now they're hiring 160,000 people per year with a huge turnover and they're using XOR for this. They're still our customers, they're still very happy.
Joel: Aida, you service 103 languages you said, I think that's amazing. How did you do that, and you said most of your competition just covers a couple languages. Get a little more specific about some of your competitors and how they fall short of servicing so many languages.
Aida: Yes. Actually my technical co-founder is a pretty impressive guy. He's been in software development for 16 years, managing all types of teams, so he won the national wide competition in AI chatbots back in Russia two years ago. That's when I found him. So the way we did it is we don't use the Microsoft LUIS or IBM Watson, we built our own proprietary chatbot engine that actually works in two main languages, which is Russian and English, and then above that we use little twists and tricks and know-how with the use of Google translate.
Chad: Gotcha. She just said Watson sucks. I love it.
Joel: Competitively, who would be in second place with the second most languages?
Aida: The two main languages that mostly used are English and Russian right now.
Aida: And Spanish as well. Now we're getting actually traction in Brazil as well. So yeah, we're doing this very big partnership with Brazil.
Joel: But you know your competition, you know Mia, Olivia, AllyO, etc. What kind of language penetration do they have outside of English?
Aida: I believe all of them cover English for sure. I don't ... I'm not aware of any other languages. I do know some of the competitors also cover, for example, Dutch or German, but none of the rest.
Chad: Okay. So what messaging platforms do you actually connect into? I mean, what if I'm on a mobile phone, I'm in an Uber, I'm actually going through the process of applying and I've arrived at my destination, I close the browser. What happens next? Have you lost me? Does it go to my ... Did I choose to use Facebook Messenger? Is it text? Tell me how you don't lose those types of individuals.
Aida: Absolutely. So first of all, we do use our web app. Of course, that works with any browser on any device. This is the first one. We also connect all the data of all the candidates from the moment they apply in order to re-engage with them, to confirm the meeting, to give them the opportunity to reschedule, so we're using pretty much emailing, texting, Facebook Messenger, Telegram messenger, Viber, Skype. Now we're adding WhatsApp because they just released the chatbot API, finally. But new ones are web application and combined with the texting.
Joel: You say that you, in your promo video, that you integrate with every ATS and every digital calendar system. Certainly not every one, right. Talk about that.
Aida: Yeah, sure. So we're integrated with the most popular calendar systems, obviously, because scheduling is everybody's pain point right now, so this is Google calendar, Outlook Microsoft 365, and as for the ATS, we are currently integrated with 12 of them and we build integration as we go so that means as we acquire a new customer, if they need a special integration, we do that. There are like all the mainstream ones and also we are integrating with a whole bunch of congruent ATSs that our customers are using, obviously. As for the mainstream ones, it's Taleo, SmartRecruiters, iCIMS, Greenhouse, Lever, and a coupe of others, TempWorks, JazzHR, I need to kind of recall them, but 12 of them altogether.
Chad: So as we take a look at, I mean really, the globe, there are plenty of places for you to attack and really gain amazing penetration, so like Russia, Europe, so on and so forth. Apparently you guys are really going to focus on the US market. Why move to the US market so quickly without just going ahead and owning Europe and Russia and Asia, etc?
Joel: Middle East.
Aida: Let me tell you that US market for HR technology is 300 times as big as in Russia, for example. So it's the biggest market as well as the obvious step for us to go. Also, in the US in a couple of industries, five industries, they do experience a very high labor shortage right now, labor crisis they would say. Industries such as construction, which is booming and they cannot hire people fast enough, health care, retail, restaurants, and hotels. This is why we're focused on the US, because the unemployment rate is so low, they need to do something about it.
Chad: Gotcha. So there's just the opportunity. I mean, obviously the dollar amount is ... that's a nice little draw, but also the opportunity because it is so hard, especially right now in the US to recruit. That being said, high volume recruiting is something where you guys have focused. How do you serve, because that's a big change going from high volume to a corporate more of like a white collar professional type of a platform, how do you serve both sides and do it well?
Aida: Yeah, absolutely. We started with high volume recruitment, because there we saw the immediate results for the customers, obviously. But when we started to penetrate the American market, we actually even shifted a little bit more to being the industry agnostic system because we're currently working with a technology company, with staffing agencies that are hiring white collar types of jobs, types of people, so it doesn't really matter. We'll automate the same things for them, asking the filtering questions, we prescreen them, then we schedule them, answer their questions.
Aida: The only difference is that maybe in FAQ part of the chatbots. For example, if we're talking ab the white collar types of jobs, we are mostly focused on what's my career development, the Visa support, internship programs, so on and so forth, whereas for the blue collar, it's a little bit more straightforward, because ... what my salary will be, will I have to wear a uniform, will I get a corporate car, so on and so forth.
Joel: I want to ask you about onboarding. You mentioned in your promotional material that when someone becomes a customer, one of your "AI team onboarding members" will call them and go through questions, etc, which to me one of the big issues with chatbots is one of scale. They all have to have a human involved to build the Q&A and hand hold for a little bit. Do you ever see your company getting to a point where's not a human onboarding team involved? That it can be turn key or just some basic questions that a company needs to fill out or answer?
Aida: Absolutely. We are actually working right now, so first of all, we do have a huge database of library templates that we use, and we also edit them and also launch them as fast as we can. Our custom success managers do that. But, right now we're serving enterprise customers and staffing agencies as well as high volumes of types of jobs, but we do think that our solution is something that every company with over 50 people could have benefit from. So for those types of people, we definitely will build the kind of ... we're actually right now working on a system that will turn the job description requirement parts into the chatbot right away for those smaller companies that will be able to do the onboarding themselves.
Aida: But right now how it works is our technical team and our customer success team are working together, so custom success team is working closely with the talent acquisition team of the customer in order to build up the chatbots in order to set up the initial knowledge base of the chatbots in order to build out the filter questions for every type of position. The technical team is taking care of the integration with ATS and calendar system.
Chad: How are you actually attacking the market, because attacking the high volume market is entirely different than attacking the blue collar kind of more corporate type of market. So how are you attacking the market from an education and a sales standpoint?
Aida: As for the sales, it's pretty straightforward. It's B2B sales process. The prospecting emails, qualifications, demos, proposals, the usual thing. So as for the educational market [crosstalk 00:19:58]
Chad: Fortune 500 companies right out of the gate or are you using partners to be able to facilitate that process?
Aida: We do both, but we do see for sure that the most reliable way source of leads for us is prospecting and the cold emailing if you can say so. But the partners is another way of ... for example, the partnerships with a couple of ATSs that we're currently working with. Yeah, this is very interesting for us but you cannot really scale it up and it takes a little bit longer.
Joel: AI has been under fire in recruitment lately. You've probably read the story about Amazon.
Aida: Oh yeah.
Joel: Building their own AI component and the bias was sort of starting to build in to the platform or the application. In your materials, you talk about your own AI and the more that it's being used, it learns and it starts recommending who might be good candidates for jobs. So talk about that solution that you guys have and how you keep bias out of your solution, whereas Amazon failed.
Aida: Actually as for the Amazon, let me add the little comment you can ... I do not believe they actually launched it and somebody was discriminated, although ... and I also cannot believe that they couldn't exclude the feature of the gender out of the equation. That's very interesting for me. But at the same time, so the predictive analytics of the chatbots is another very big component where for usage of which you do have to have very big data set. So we're currently ... what we're doing right now is we build out the predicted analytic that will let you ... based on the number of metadata that you gather about the candidate from the moment they apply and based on historic data, what types of candidates were successful in the company in two ways, were they ever promoted, and how long did they stick with the company, will predict not only the level of engagement of the candidate and the score based on hard skills and how many years of experience and education and so on and so forth.
Aida: But also, how likely will the candidate turn out within three months, or how likely will the candidate be recruited or stay with the company for longer than a year? That's one aspect of predictive analytics and the second one is how fast do you need to move with this candidate in order not to lose him to the competitor and that makes sense. That's also extremely important for us.
Chad: It certainly does. So let me ask this just from a clarification standpoint. You are looking to do transactional type of business with employers who are like under 50 employees, and then you're also looking to try to go after top notch Fortune 500 companies at the same time. Is that what you're doing today or is that what really your long term focus is?
Aida: It's our long term focus, because right now our main focus is enterprises and staffing agencies.
Chad: Gotcha. So go back to the partner strategy kind of conversation. So we've seen Paradox and Olivia do some pretty smart partnerships, like one with SmashFly, where they have Emerson automatically embedded into a platform that is already serving hundreds, hell, who knows, even maybe thousands, of employers currently. So that was a just add water kind of scenario. What are you doing beyond the applicant tracking system side of the house to be able to create those types of partnerships to really drive adoption?
Aida: Right. In order to drive the adoption, first of all we do the partnership with the ATS which is the most obvious way because the chatbot is the thing that stands between the job board, so whatever the job distribution channels are, and ATS, and automate this engagement with the candidates, right.
Aida: You also mentioned Olivia and Paradox, which I think is the same thing, right?
Chad: Yeah, yeah, but they've partnered with SmashFly. That was my point. They partnered with SmashFly.
Aida: That's a good one. We don't do any of those types of partnerships, if that makes sense, right now.
Aida: That might be a good idea.
Chad: And I mean, so right out of the gate, the applicant tracking systems really haven't given a shit about candidate experience at all.
Chad: So having the opportunity to embed the chatbot into an ATS, that's all well and good, but why wouldn't you focus on trying to embed into an actual candidate experience platform? That's what they're there for.
Aida: Yes. That's right, but ... that's a good point, actually, but we don't really believe in the partnership between the ... I don't know. When we're in the early stage startup, not early stage anymore, but at the same time, we do know that the main focus should be at the customer acquisition currently to do the partnership on the same terms, if that makes sense.
Aida: There will be benefit for both, for the commercial standpoint and from the ... yeah. So that will not be sole dependent on the partner in that point.
Joel: I want to ask about Ikea. It looks like you guys are doing some work with them and what I found interesting was you did some sort of a kiosk program with Ikea and we think so much as chatbots as either a desktop application or something on your mobile phone, but I think kiosks is pretty interesting. Tell us about what you did with Ikea.
Aida: Absolutely. So with Ikea, we do the kiosks. It's in every Ikea, there are a couple of ... you could say it's an iPad, right?
Chad: Mm-hmm (affirmative).
Aida: So any person could just go up there and just apply for a job. Pick a job that suits to this particular person the best, find a location that's closest to their home address, and then apply for a job, go through the prescreening and be scheduled for an interview right away. That's the idea for that. But what we also do in terms of the ... it's gonna all fly in chatbots, if you can say so, it's not an online source. You go by hands ... you go by feet and then you feel it out.
Aida: We also do ... we have a couple customers in retail, we also need experience with scanning of QR codes, which are not that huge in the US anymore, but they are pretty still used in Europe, so you can just scan a QR code and get to talk to the chatbot right away from your mobile phone. For example, for students at job fair or something like that.
Joel: Gotcha. So as we're sort of winding down here, tell me about pricing, and I want to know about your ultimate goal for the company. You've taken very little in money so you have some flexibility. Do you want to grow the company and have it for five, ten years? Do you want to flip it here in the next one or two? What's the ultimate goal and what's the pricing of the product?
Aida: Absolutely. The pricing, it's SAAS, it's an annual subscription which depends on two factors, first one is how many applicants the company is processing per annum basis, and second one is what are the feature set, what are the business process they actually want to automate? For example, whether or not they want just basic scheduling for the first step of the interview process as opposed to the complex scheduling with all the hiring managers, panel interviews, sequence interviews, and so on and so forth. Also whether or not they will need the video interviewing functionality, the widget on the websites, and ... yeah. It can reach anywhere from $30,000 to $600,000 in the US alone, so that's the pricing.
Joel: And ultimate goal?