Death Match: Aida Fazylova w/ XOR

Welcome to Death Match, North America 2020, GRAND CHAMPION EDITION which took place at TAtech on May 19. For all of you NOOBS who have never experienced Death Match - Death Match is a competition which pits 4 innovative, early-stage companies against one-another, only one can win and emerge with the coveted Death Match Chain of Champions.

This Chad and Cheese Death Match episode features Aida Fazylova founder and CEO at XOR that's X-O-R people. COVID-19 might've locked us all in our homes but never fear! The home bars are always stocked, pints were flowing and Chad and Cheese questions and slurring snark was flying. Luckily Joveo's CEO, KJ, stepped in to provide a smart and sensible judging voice to this TAtech event...

Enjoy while Aida reaches down deep for her inner Ivan Drago pitches XOR, then ducks, bobs, weaves and lands a knock performance during this virtual Death Match event. 


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Intro: Hide your kids, lock the doors, you're listening to HR's most dangerous podcast. Chad Sowash and Joel Cheesman are here to punch the recruiting industry right where it hurts. Complete with breaking news, brash opinion and loads of snark. Buckle up boys and girls, it's time for The Chad and Cheese Podcast.

Chad: And we're back people. It's Death Match, North America. Today we have Aida Fazylova.

Joel: Aida.

Chad: CEO, and founder of You have two minutes to pitch, Aida, are you ready?

Aida Fazylova: I am.

Chad: Let's do it.

Joel: In three, two.

Aida Fazylova: My name is Aida, I'm CEO and founder at XOR. XOR is a AI powered communications platform that let's the recruiting teams, as well as HR team to hire the people and retain the talent much more efficiently. What I mean by this is that on one hand we give them the opportunity to communicate with their candidates over the text, as well as in the messaging apps, to get them to the 46% of the response rate within 15 minutes. And on the other half, we give them the opportunity to utilize artificial intelligence, to automate the most routine repetitive processes in talent acquisition and HR. I'm speaking about the passive candidates reengagement, screening of the inbound candidates, everything around the interview scheduling, referral partnerships, virtual interviews, video interviews, recordings, and so on and so forth.

But also a bunch of the things throughout the employee life cycle, starting from the inbound candidates, from the onboarding and the orientation of the new employees to poll surveys, to also staying engaged with the people that got laid off or to the exit interviews. So yeah, as you know, this is a new reality that we're going through in the last two months. And there are four main categories in the markets, the people that hire talent at higher pace, the companies that are hiring at the same pace that are dealing with the huge amounts of the applicants due to very high unemployment level, as well as the companies that do need to stay engaged with people that they have laid off, just in order to, once the economy start kicking again, to rehire them quickly. We've been around since 2016. We serve nearly 200 customers in 15 countries right now, headquarter here in San Francisco, California. And the company was born out of my personal theme because I used to work as a talent acquisition practitioner, for nearly a decade in my career. And the company itself was born out of my personal theme, that's about it. Yeah, I think that's about it for the pitch. Thank you.

Joel: Tell them where they can find out more.

Aida Fazylova: It's

Chad: Excellent.

Joel: All right.

Chad: There you go. All right, KJ, you sir have the first question. How about it?

KJ: Thank you. A simple question. What does XOR stand for? It's a very unique name.

Aida Fazylova: I didn't catch this. Sorry, could you repeat?

Joel: X-O-R, what's it stand for? What's the meaning?

Aida Fazylova: We're saying to everybody that it stands for extraordinary optimized recruitment. But actually also it's a binary operator called exclusive or, so very geeky stuff, but extraordinary optimized recruiting is about right.

Chad: Nice. Okay. Well, we'll go ahead and jump into the hard questions. Are you ready?

Aida Fazylova: Yeah.

Chad: The messaging space is bloated. We have companies like Emissary, TextRecruit, Canvas, TextUs, Talkpush, AllyO, Mya. AMS just came out with their own conversational platform. And Paradox just got $40 million in series B funding. Why should anyone know about XOR? I mean, there's so many that are out there. How can you separate yourself from all of those names and all of that money that's being spent?

Aida Fazylova: Yeah, absolutely. Very good question. There are two components to XOR. On one hand there's the texting, as well as the other hand there's automation and conversational interfaces throughout the recruiting, right? As I understand right now, we're at very new and emerging fields, still the market penetration of any automation or the conversation right now is very well under 4%. The texting is a little bit higher, which is great. A couple of things that really distinguishes XOR from everybody else. First one, we support 103 languages on very, very great level. So that the companies can actually use this globally. Second one, we are actually the great of the older messaging platforms like WhatsApp. It's not only the texting, it's not only the widget on top of the company career sites. It's also the things like WeChat, the Line, the WhatsApp, the Viber, Telegram, Facebook, WeChat, you name it.

Third one, very important one for XOR is the scheduling functionality that we have. We actually handle very complex scheduling scenarios starting with basic one on one meetings with the recruiter, with integration to all the calendar systems out there. But also more complex scheduling scenarios, like many on ones, one on manys, panel interviews, sequential interviews with automated updates of everybody's calendars and management on this. Third one is very easy to manage, the third or fourth one, very easy to manage the chatbot workflow that can be done pretty much [inaudible 00:07:42.22]. But also an ability to utilize either fully manual texting, fully automated texting or something in between like hybrids. When the recruiter can actually carry on the conversation with the candidates, from our interface, which looks like a Gmail for texting or to the messaging has changed in any of the messaging apps, but also let the chatbot take over some of the repetitive processes such as scheduling, screening, answering the frequently asked questions and then orientation of the candidates picking themselves the job.

Chad: Who's your target market? Is it enterprise or is it SMB?

Aida Fazylova: Actually companies as small as 300 employees are using XOR. It can be used by staffing agencies and it can be used by enterprise as well as the SMBs right now. We give the functionalities to everybody. And it's also very industry agnostic because obviously we started with a high volume type of recruiting in retail, hospitality, fast food chains, because this is where we saw the majority, the most of the value. But as we're moving through our company life cycle, we're becoming more and more of the industry agnostic. It's not necessarily only high volume or blue collar types of hourly workers, but it's also engineers. It's also healthcare employees as well as the white collar type of jobs.

Joel: Chad was quick to point out the funding that some of your competitors have gotten. And I want to give you an opportunity to talk about the funding that you've gotten, but more importantly, what are you doing with that funding? Particularly with marketing, it is very crowded space. How are you cutting through the clutter and getting through? Are you guys integrating with ATSs and other platforms? And what has it meant for your talent in terms of who you've been able to bring on to the company?

Aida Fazylova: Absolutely. That's very good question. I'm dying to tell you about us. We as a company have been very much grown organically for the first two years, because we started from Eastern European market. Obviously with the venture capital market there is very

immature. We actually got funded last year. It was seed round of $8.4 million in total, led by a San Francisco based venture fund called SignalFire. SignalFire was a lead investor in TextRecruit before. TextRecruit as you know got acquired beginning of 2018. By the time we met them, they actually exited from the TextRecruit already, which was really great. But they were actually really, really aware of the space. They did know the space very good. We are headquartered here in San Francisco, although we keep the back office and the development elsewhere, namely in Eastern Europe, which allows us to be very cost efficient and lean.

But what we've done with the funding as well, we have been using this for them, sending up the executive team here in San Francisco. From them we actually hired the VP of marketing as well as the VP of sales of TextRecruit, which is really great, that are leading right now our sales and marketing efforts. Yeah. So in terms of the integration within ATSs, I've already mentioned that XOR ... I didn't mention this. But XOR is not a replacement within ATS. It sits on top of the existing technical stack, whether it's an ATS or CRM, as well as the calendar system, as an AI powered communication layer, if you please. You can use it without XOR's interface at all, or you can use XOR's interface for the communication with your candidates. We have prebuilt integration with nearly 30 applicant tracking systems, job boards, as well as the CRMs at this point, as well as the integration with all the calendar systems out there like Google Chrome, Microsoft Office 365, Outlook, as well as the on-premise exchange service.

Chad: KJ.

KJ: Sure. Aida, .ai means that you have artificial intelligence in that. And what it means is that when you interview a person through a chatbot, you are not working off predesigned flows or the flow chart for that matter. That question leads to this question and so on and so forth. But the system is smart enough to understand what those questions are. And so it's not only you know right question. First, how do you do that? And second is, what's your feedback loop that goes back into designing another question that's better.

Aida Fazylova: Absolutely. That's very good question. We are using AI in a way of natural language processing as well as for the analytics, so they're strategically. It's still more about the robotic process automation as you know, augmented with AI, right? So that we understand what is there. If the candidate is asking the chatbot a question, in the FAQ section, for example, it actually recognizes the intents and gives them the best response from the knowledge base of the chatbot. Or when the candidate types in the response to the chatbot question actually recognize what was the response and also assigns them, let's say through the screening process, it assigns them a certain score as they're moving through the screening process, right?

KJ: No, if you're deploying an LP and there's a bit of a deep learning into that, then it's very difficult to do that in multiple languages. I was kind of intrigued in how you really truly are global in that sense.