In a candid interview, Itamar Arel, a seasoned entrepreneur originally born and raised in Israel, shares his fascinating journey from being a computer nerd in his early days to navigating the worlds of academia, startups, and corporate acquisitions.
His latest startup, Tenyx, has attracted funding from top-tier investors like Point72 Ventures, AME Cloud Ventures, Morado Ventures, and Coelius Capital.
In this episode, you will learn:
- Itamar Itamar’s journey showcases the transition from academia to entrepreneurship, driven by a passion for translating cutting-edge machine learning ideas into real-world applications.
- Apprente’s groundbreaking vision of automating drive-through order processing in quick-service restaurants led to its acquisition by McDonald’s, marking a significant intersection of technology and industry.
- Itamar’s experience underscores the resilience required in the startup world, navigating challenges, and adapting to changes in leadership, ultimately leading to the reacquisition by IBM.
- McDonald’s acquisition of Apprente included the vision of establishing a Silicon Valley Center of Excellence for intelligent automation, showcasing the importance of technology in traditional industries.
- Itamar Arel’s entrepreneurial spirit continued with the creation of Tenyx, focusing on leveraging large language models for building human-like, robust voice AI agents for automating customer service functions.
- With a successful track record, Itamar secured $15 million in seed funding for Tenyx, emphasizing the importance of market validation and refining ideas based on customer feedback.
- Itamar envisions a transformative future where voice AI automates the majority of customer service calls, significantly improving customer experience and operational efficiency across various industries.
For a winning deck, see the commentary on a pitch deck from an Uber competitor that has raised over $400M (see it here).
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About Itamar Arel:
Itamar Arel, Ph.D., M.B.A. is currently the CEO at Tenyx, formerly a professor of electrical engineering and computer science at the University of Tennessee from 2003 through 2013, and a visiting professor at Stanford University’s AI lab from 2013 until 2015.
In parallel to his academic career, he co-founded both Binatix – one of the first companies to employ deep learning technology to financial services, and Apprente – that built voice-based AI conversational agents for drive-thru at quick service restaurants (acquired by McDonald’s Corporation and subsequently by IBM).
Itamar recently held the position of corporate VP and head of McD Tech Labs at McDonald’s Corporation, and head of conversational AI at IBM Watson Orders.
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Read the Full Transcription of the Interview:
Alejandro Cremades: Alrighty hello everyone and welcome to the dealmakerr show. So today. We have a really exciting founder. You know a founder that has done it quite a few times you know and successfully sold and he is from startup nation originally from Israel. We’re going to be talking about. You know, building scaling financing integrating. You know the company once is acquired by a large player. They sold the last company to Mcdonald’s and then also challenges you know as well with a big company versus a small company going through rounds of financings. All of those good insights that we like to hear so without furtherdo. Let’s welcome our guest today ittamar rl welcome to the dealmaker show so originally born and raised in Israel so give us a walk through memory lane. How was life growing up there.
Itamar Arel: Yeah, thanks so much for having me.
Itamar Arel: Yeah, 1 raised in Israel is kind of a computer nerd from as as far as I can remember. So naturally you know coded very early at a commodore 64 and a commodore amiga if anybody remembers those machines and then eventually. Ended up naturally gravitating to studying computer engineering in in college and then grad school and and so on and so on so it was great. It was a great time to to be a computer nerd.
Alejandro Cremades: So what about coming to the Us How did that thing happen. How do you land here.
Itamar Arel: Yeah, so following my ph d which I also did in Israel I sort of wanted to pursue an academic career and so start a postdoc at Stanford this is this is pre. The 2012 Ai machine learning revolution so much smaller community did early work in reinforcement learning and then. Um, sort of in what was kind of life takes you and all sorts of weird directions ended up taking a faculty position at the University Of Tennessee in Knoxville also an computer engineering program and there for you know about 10 years they’d work in reinforcement learning some robotics even and what later became the field of deep learning. It was ah it was an exciting like I said much smaller community but very exciting time to to do that kind of work.
Alejandro Cremades: So tell us about also going to startup land you know which is really being in Stanford and seeing all the innovation around you too and and all the all the different startups that are flourishing. You know how was that moment as well for you to. Venture into the startup world because you did that at the same time in which you were exploring academia.
Itamar Arel: Right? I I think in retrospect I was always intrigued by taking so the latest and greatest ideas in machine learning of course and trying to even push them further and see what kind of products and services they can they can deliver in the realworld. You know the impact that’s not to say that academic work or scholarly work. Ah. And publishing papers is is less exciting but at the end of the day I think I’ve always been kind of passionate about what could be built with these technologies and you’re right. Stanford is 1 of those places where almost every faculty member just being in the epicenter of Silicon Valley every faculty member is is involved in some kind of entrepreneurial. Activity. But yeah, so so during my academic career I was involved in several companies that made use of machine learning in one domain or another sort of split my time academia and and that kind of entrepreneurial activity. One of those companies was an early company called bionatics was a. Early company that made use of machine learning in financial analytics signals for financial trading and things of that nature. It was very interesting to think about that you know that time again which wasn’t that long ago versus now the tools that that were made available were much more limited. You need to. We needed to code our own kuta code and and develop algorithms almost from scratch. Um, so that I think was one of those experiences that got me excited about what could be done with machine learning in in the real world and then after 10 years and ah in in academia decided to take 2 years of sabbatical and I was fortunate to have a.
Itamar Arel: Of courtesy appointment the visiting professorship at the Stanford ai lab I worked with sylvio saesa on a fairly large Darpa project. We had Syviville of course at the time was ah was a professor and since took the role of chief scientist in salesforce um, and and after a couple years there decided. To leave academia leave tenure which is an uncommon move and or give up tenure and and turn to to the dark side or the light side and have been been in several companies since.
Alejandro Cremades: So at what point do you realize that maybe Academia is not a path for you to follow.
Itamar Arel: I think I felt at some point and I’m I’m sure I’m not the only one that a lot of the this is mostly post 2012 the sense was that a lot of the exciting work certainly more in the applied research side of things in the in the field of machine learning and ai. Was was somewhat shifting outside of academia either to large corporations like Google and Facebook that have the prominent research and applied research teams or or startup small companies that want to do something unique in in some niche. Um, and. And and I think at that point you sort of have to make a decision. Do you stay in academia or do you try to to maybe switch to to one of those settings and at some point it became clear to me that that that’s what I wanted to do. It’s interesting as an. Academic particularly on the research side part of your job is to to have graduate students and train them essentially train the next generation of of researchers particularly ph d students and and there’s a lot of satisfaction and fun in that at you know the first. 2 3 years you you sort of you teach someone how to become a researcher how to approach a research problem and then they hopefully at some point take off and and find their own topic and write a dissertation about it and so forth. Yeah I found an industry. It’s it’s different in in our so in our field particularly in deep tech ai.
Itamar Arel: Again either startups or large organizations you you sort of have the the output of that you typically have a group that has a numerous number of Ph D folks with Ph Ds that have the experience. So yeah, they’re already trained to be good hopefully applied researchers and and you can run fast and you could do. Kind of things that that are just difficult to do in Academia the academic life just naturally has a different cost function if you will. So yeah, there’s not good or bad. It’s of course a very personal decision I Just I was just very excited about the latter and what could be built with a strong team of very motivated and and smart people.
Alejandro Cremades: So then so then for you, you ended up going at it and ultimately the company that you ended up going at it with was a cola Apprte which ended up being a pretty interesting. Um you know, outcome too. But.
Itamar Arel: Um, yeah.
Alejandro Cremades: Walk through what walk us through you know what were the sequences of events that needed to happen for you to bring a printer to life.
Itamar Arel: Sure, absolutely so after making the decision to leave academia I actually was fortunate to join a fund as an eir an entrepreneur in residence. This was at the ame cloud ventures which is the fund started by ah Jerry Yang of course started Yahoo I’d I’d know. Folks from that fund and and it was just ah, they they offered this opportunity and you know being an yeah eir is a great time to figure out what you want to do when you grow up like you know, take some time and look at maybe interesting problems out there and and and if you are. If you do have the entrepreneurial bug then it’s a great time to prepare for that and then launch a company and that was that was actually what what happened I was there for about a year and then started apprentte as you mentioned in very very early, well kind of late 16 early 2017? Um, and of course um were one of the investors. That’s also. Ah, common sort of trajectory right? If if a fund hosts you and you do end up launching your your startup then it’s not uncommon for that fund to to have the opportunity to invest. So yeah, so basically the the interesting story there is that. At apprnte very early. We had the vision of building voice Ai agents that automate the order taking process at Drivethroughs. So think Starbucks Mcdonald’s young brands you know burger king and so forth all these chains that we know and love that general space is called a quick service restaurant space.
Itamar Arel: Of course Mcdonald’s is the ah the the industry leader I think roughly about 11% of the market. But what’s interesting is there’s a long tail’s over fifty five zero chains in the us that have over $1000000000 in revenues. It’s ah so it’s a very fragmented. Very rich space. And what’s what’s even more interesting or what we found was interesting over 70% of the revenue across that whole space comes from the drive-through which is a little mind-blowing you think it’s the delivery and the sitdown restaurants. But no, apparently um, most people in the us don’t want to leave leave their truck as they as they get their food and it’s ah it’s natural. It’s sort of it’s. Inherit to that business model and when we learned that the the bulk of the revenue did come from the drive-through it made perfect sense to say well could could we automate that order taking process if you’ve ever looked at staff at these restaurants they you know they multitask like crazy a huge. Appreciation for what they do they they take orders and they make food and they make drinks and they do so many things in parallel that’s kind of it’s amazing and so our thesis was all right? Well well let’s see if there’s interest in in kind of automating that piece the order taking piece. Um, you know, not necessarily as a direct like. Cost reduction job killing thing but maybe as a way of again offloading that load from the staff so they can make more food and maybe even grow the the pie the revenue and and so we started with that thesis. We. We build our product as I mentioned we did work with with many of these changes that I mentioned.
Itamar Arel: And Mcdonald’s in particular, we were introduced to them through graylock who were 1 of our investors at the time and it’s one of those things that just timing is is everything in this but you know they they were independently sort of looking out for the the innovation team was looking to see whether this is science fiction or not whether the technology is mature enough. To have such a solution sort of automate the vast majority of the orders at the Drivethrough. Um, and and so we ended up working with them and and then piloting it it stores and so forth and.
Alejandro Cremades: And and and before before that How how were you guys making money. What was the business model of Apprentee for the people listening to get it. So.
Itamar Arel: Yeah, so it it was inherently sort of a saas model. What was interesting is and it’s true for for any enterprise use case there there is of course a cost reduction sort of cost reduction value proposition. But there’s also a huge customer improvement customer experience improvement component to it. Ah, with Mcdonald’s it was literally to try and quantify both the cost. The potential cost reduction and the the potential revenue ad like I said if you if you free up staff at the at the restaurant they can make more food they can. They can do other things that they multitask like crazy around. Um, and and and generally even just improve the customer experience by not having for example, customer wait too long right? If the if the average order time gets shorter because again the staff is freed up to do other things that results in in more volume and and just overall better customer experience. So with them if the Calculus was Mcdonald’s has 14 plus. Ah, thousand stores in the us and about 40000 stores globally and so you do the numbers any significant cost reduction that translates to to a meaningful number. Um, yeah, it’s it was it was quite quite an adventure and.
Alejandro Cremades: Because prior to the transaction actually happened. Um you were talking about graylock I mean incredible. We see how much capital Do you guys raise right? before the transaction.
Itamar Arel: Yeah, so we raised about $5000000 as a seed round and then at is interesting story there as we were preparing to do our sort of series a or conventional price round series a at that point we were already fairly far along engaged with Mcdonald’s. To the point where we had a poc that was a paid poc and we were paid paid. Well certainly in in in startup terms to the point where it just made sense to maybe do another seed which was essentially what we did to. Bridge the process not necessarily from from the perspective of running out of runway or money but just to sort of see where that relationship with Mcdonald’s matures into and it and and then sort of be able to better price. A series a that we did raise that second round so all and all raise about $10000000 for printate but of course Sira never happened because at some point we were approached with the idea of folding into Mcdonald’s.
Alejandro Cremades: So so you were you were talking about this earlier graylock was the one that initially made the connection to Mcdonald’s so how did the you know how did that did the situation or the sequence of events you know. Unfolded towards the acquisition. What happened you know after that connection happened and then how did that journey translate all the way into you inking a deal to have the company acquire for for for an over nine figures I think it was reported.
Itamar Arel: Yeah, so the introduction was so the the big funds do this and I think it’s part of the true value ad that they offer they have relationships with chief technology officers and chief innovation officers across many large organizations. And periodically they invite these folks to share with them portfolio companies that they think might be interested in in what they’re building might be relevant to those big enterprise customers and that’s exactly sort of the setting through which we were introduced to the Mcdonald’s folks graylock hosted this this event where I think it was 6 or 7 companies. Not sure whether any of the others ended up kind of ah pursuing that relationship but for for us like I said this was something that was bigly on the roadmap. They were independently looking at at this I guess they were feeling like you know, maybe even at the time this was posted. The 2012 deep learning deep learning was already a thing and Ai was picking up and so I think they had the sense of yeah, maybe maybe it’s not science fiction anymore and so we we were introduced through that event followed up with some meetings. We had an early demo of what we were building and you know. Huge respect for for for Mcdonald’s A Company because one of the things they said. Okay, let’s let’s let’s make a bet here. Let’s invest some time develop this poc into something that’s pilotable and then go into a pilot in real stores and really test this thesis Mcdonald’s at the time had ah an innovation team.
Itamar Arel: Under the global technology organization whose job was primarily to do exactly that find find startups or other companies that have unique technologies that might be impact for for their business and so again it was one of those kind of perfect everything you know, timing aligns and and. Incentives align and and we ended up working with them. Um, you know it’s interesting because we were we were about a year into the to the engagement and already as I mentioned piloting our solution in stores when I got called in I met this is the second time I think I met the Ceo and. And he’s said 2 interesting things. He said you know Mcdonald’s views itself as an industry leader. Of course it is and he felt like they should be paving the way to solutions like this we we had convinced them I guess at that point that it’s no longer science fiction. This can actually be done and so definitely. Part of the reason for proposing the acquisition was to because they wanted the team and the tech and believed in what we were doing. The other part was that yeah you know Mcdonald’s felt at that point or at least that was our impression that they were behind in establishing kind of a Silicon Valley Center of excellence around intelligent automation ai much like. Walmart did Walmart Labs and at the time uber had a reputable machine learning group and and so part of the pitch to us was how do you feel about being the founding team around which will build the center that will initially focus on this voice solution but maybe beyond that grow to computer vision robotics and one can imagine what the.
Itamar Arel: The Mcdonald’s of the future store of the future would look like and and that was that was you know I took that back to the team and and that that got us excited to so of pursue continue that conversation and from there on it. It was more we wanted to know more about that like how did are we just going to be you what kind of satellite. Organization will we be and what would the reporting look like and the budget because I think again, what’s what’s always the case in these kind of acquisitions is that you know for us this was an opportunity to ah to do the the kind of things we wanted to do with the. Sort of budget that no startup can do right and we grew to from about 20 at the acquisition to almost 100 but a third ph ds you can imagine I think a budget was around $40000000 a year something of that order and again it was exciting because startups would like to do all that but they typically just.
Alejandro Cremades: Yeah, well really really amazing you know outcome you know to such a big company. You know like that and then and obviously you know like for you guys, you did the integration. You know you did the best thing for about 2 years or so.
Itamar Arel: Just can’t right? So yeah, so bunch of conversations on the road. We we ended up folding in.
Alejandro Cremades: And then you know eventually like everything you know, what’s an entrepreneur always an entrepreneur and then the idea of your latest baby comes knocking which is ten x so at what point does 10 x come knocking and why did you think it was meaningful enough for you to take action.
Itamar Arel: Yeah, so as you mentioned we were there for I guess two and a half years and then new leadership came on board and while there was still and still are very bullish about the solution I think there was a feeling that. You know, maybe it isn’t necessarily the role of Mcdonald’s to to develop cutting edge a and as a product of that we ended up being reacquired if you will by Ibm so the entire at that time almost 100 people kind of organization shifted became part of Ibm Watson and basically I you know ah saw through that transition and so forth, but to your point when when you’re hit with the with the startup bug at some point particularly after 3 years in corporate setting when there’s a lot to learn and how big organizations manage these large projects and so forth I I missed. Ah, being in the small team that that wants to do something kind of novel and change the world in some particular way and so shortly after the transition to Ibm when everything was stable and running started 10 x which was about two years ago
Alejandro Cremades: So then tell us about 10 x you know what are you guys doing at 10 x.
Itamar Arel: So many ways. It’s a continuation of the philosophy I’ve always been a big believer that voice is a most natural way to communicate if you can only build machines that understand us robustly with the million different ways we have of asking for things or conveying. Information and you know when we speak we we speak very different than we text we use poor grammar and broken english and so forth and traditionally that’s been challenging to build with machines but the sense was particularly around that time I guess 2020 2021 um, some of us knew about. Gpd or large language models coming out and so forth the sense was that finally the pieces of the puzzle were there and the technology side to build solutions particularly on the enterprise side that fully automate customer service functions. So if you in the us there’s over. Over 100000000000 a year that’s being spent on voice customer service which is which is mind-blowing and traditionally it’s just again, been challenging to to build anything that that even approximates human level conversation and and by the time we start at 10 x the the strong sense was all right. Now finally, it’s ready so we are building again these human-like robust voice Ai agents to automate customer service functions for the enterprise particularly call centers even more specifically started with travel and hospitality so hotel reservations car rentals things of that nature.
Itamar Arel: And then kind of expanded to real estate and and some other verticals there. There’s really a lot of opportunity if you’ve called any of your favorite airlines recently or shipping companies and so forth. You’re usually greeted by this this ivr kind of outdated Ivr system. It’s very brittle. It doesn’t really get numbers. Well, it certainly doesn’t get. Anything if it’s not very accurately conveyed and again the census in 2024 we should be. We should be able to do a lot better and so we’re kind of on the mission to to introduce almost human-like very robust solutions that. Yeah I don’t know about you or most listeners in in my case, 90% of the time early on in the conversation I press Zero zero zero just ask for representative and I I do believe in the next two three years there’ll be a transition where it’s going to maybe flip like eighty ninety percent of the calls will be automated by a very. Intelligent and robust voice ai and maybe fifteen twenty percent will be escalated to so the long tail of of questions and cases that get escalated to people and so yeah, so part of it is the introduction of large language models other. Parts have to do with with some I p some technology pieces we felt we can. We can work on and introduce some novelty to come up with a solution that that can really automate again. Customer service function across many verticals on the enterprise side.
Alejandro Cremades: So for this company you raised a fifth you you guys have raised about $15000000 so I guess the question that comes to mind here is how did you guys go about raisingcing money differently this time around since you had the experience with Alaska.
Itamar Arel: So luckily we had very supportive investors last time around and some I’ve known from even before and frankly when when when you’re successful once or twice and those investors tend to believe. You know they should bet on you again. Whether that’s always true or not. You know who knows. But yeah, certainly I mean I would admit it it is easier to raise money with with some success on your track record. So you know we approach most of the investors we had before we said look this is an exciting very large I know every startup says we have a multibillion dollar opportunity but here really in this voice Ai customer service base. There is a huge opportunity and like I said at the time it was clear that large language models are going to be transformative and really kind of enable solutions that finally finally create the right customer experience and yeah and we we knew we needed the runway to to. Build the team build the tech and engage with the first customers. Good investors primarily want to know what you need the money for not in terms of time or people but like what are the business milestones or other milestones that you want to achieve with that money and if they’re convinced that. Certain amount x is needed for you to hit those milestones and that would put the company in in ah in a good position to grow and and and raise justify higher value significantly higher value should beyond that then then they tend to to get on board and and that was kind of the case we said we needed a long enough. This is an ambitious endeavor. Um.
Itamar Arel: And and we need the runway and and we want to want to you know, go after something big and we’re fortunate to to as you said raise $15000000 as as a seed round essentially.
Alejandro Cremades: Well, let’s go and talk on the double click on that on on on on what the future is going to be here on that next thing big thing know that you were a sharing with investor So when it comes to vision. You know, imagine if you were to go to sleep tonight and you wake up in a world where the vision of ten X is. Fully realized what does that world look like.
Itamar Arel: I think all of us evolutionary are used to speech again. Speech is just the most natural way to communicate so we would love to pick up the phone dial a number if we need some service some question and and immediately be greeted by. Someone or something that understands us and and gets the service through that doesn’t exist today very recently I traveled with one of the airlines that I should travel here out of San Francisco and you know it happened to be There’s some weather and storms and if you’ve ever called during that time. It’s not uncommon to wait like 45 minutes until you actually get a person on the line right. And then when I did get the person this this lady was very kind and within 30 seconds 45 seconds anyway you needed to move flights or something of that nature and I remember leaving wow yeah, this can ain’t fully be automated now. I’m definitely convinced. The technology is there and. You know setting aside the cost reduction aspect aspect just customer experience I mean nobody likes to listen to soothing music for 45 minutes right in and it’s in some domains particularly government where they’re super understaffed if you have family members older members that try to call social security or medicare I mean it’s it’s it’s notorious for like. 3 hours on the line until you get a representative and it’s not their fault. It’s just to get understaffed a lot of so we think that again the vast majority of those calls can be serviced without waiting time you call and you you talk to a machine and you ask about this and when does this expire and can I get a copy of that and it fully handles that and so.
Itamar Arel: Um, the other thing from our client’s perspective doing things like a b testing like trying a different narrative different response to a question tomorrow that might be more informative or somehow somehow better valuable from the business perspective doing those kind of things with people’s just. Challenging. You have to convince 5000 people somewhere either in the us or the Philippines or wherever they happen to be to say something different tomorrow. That’s again with machines super easy with people. it’s it’s challenging um so yeah, a b testing analytics. All these things that go beyond just the potential cost reduction value proposition seem to be a very compelling. Overarching kind of business story for for almost every enterprise. So any mid-size to large organization either manage their own call center or outsource it through something called bpos these companies that that outsource that manage call centers for for other companies and like I said it’s one hundred billion plus year industry today. And with with varying degrees of of of customer experience and we think over the next two three years that’s going to be just totally revolutionized.
Alejandro Cremades: So then here we’re talking about the future I want to talk about the pastor with the lens of reflection if let’s say I was to put you to a time machine and I bring you back in time maybe to you know to that moment where you were still in academia you know, figuring things out on the venture side. Maybe you know, even right before. In Ats and let’s say you had the opportunity of having a chat with that younger self and being able to tell that younger etamar one piece of advice before launching a business. What would that be and why given what you know now.
Itamar Arel: I think the biggest thing I’ve learned since over the years is that you you can’t be too often or too frequent or too engaged with with talking to customers what one of the mistakes everybody makes I made the same mistake first time around is just being drinking your own kool-aid being. Just in love with your idea and and be convinced that the market you know what the market wants and there’s no reason to interact with it because once you’re out with that solution. Everybody will think it’s the greatest thing since slice spread and you learn that that’s that’s very very rarely the case and what you need to do is just very early even before raising money. To the extent you can reach out to potential customers to think that the people who might be tangentially interested in this and and validate your thesis and and refine and refine and refine because when you do go to raise money the more educated the more informed from the market you are. Ah, the more respect you’ll gain from from investors because they’ll feel like you’ve you’ve done the right due diligence you’ve done the homework. Um and and you’re not just a guy with a dream which there’s you have to be a guy with a dream but a guy with a dream that actually validated the thesis I think that’s that’s the big thing that we’ve learned or I’ve learned through that experience. The other thing is. As a Ceo particularly as a founder. Always you’re a storyteller you you sell your vision to your point you sell your ideas. It’s either to investors or potential hires or customers and so refining your storytelling I guess skills and and really polishing.
Itamar Arel: But it is that you want to convey as a vision I think that’s that’s critical.
Alejandro Cremades: Amazing So itamar for the people that are listening that will love to reach out and say hi. What is the best way for them to do So that’s right.
Itamar Arel: Ah, to reach out to to me? Yeah, well, it’s my first name eatmar at ten X Dot Com happy to to help anyone? Yeah, certainly if you’re an entrepreneur and you’d like advice to the extent that I can offer something valuable happy to do so.
Alejandro Cremades: Amazing! Well hey easy enough what hey Tamar thank you so much for being on the deal maker show today. It has been an honor to have you with us.
Itamar Arel: Thank you! Thanks so much for having me.
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