Vested Capital
Vested Capital

Episode 13 · 4 months ago

(EP13): Marcel Herz Co-Founder And CEO Tiliter, Computer Vision Startup Disrupting Retail Checkout

ABOUT THIS EPISODE

Marcel Herz is co-founder and CEO of Tiliter, a company that is accelerating the democratization of computer vision.

Presently they are focused on the grocery store industry, offering a device used at checkout to scan and identify fruits, vegetables, baked goods - anything that is loose without a barcode.

This is just the tip of the iceberg however, as you can imagine being able to scan and identify real world objects will have countless applications, especially as the software gets better and quicker.

I made a small angel investment in Tiliter via the AngelList platform led by Brendan Hill, a previous guest on my podcast. I'm excited by the traction Tiliter already has - currently in hundreds of stores around the world - and also where this technology is heading.

You can listen in to this interview to learn how Marcel and his co-founders built the prototype of the Tiliter checkout, then began approaching large grocery store chains to test it out.

Enjoy the interview.

Yaro

Podcast: https://www.yaro.blog/pod/
Blog: https://www.yaro.blog/

Hello, this is yaro and welcome tovested capital episode number thirteen featuring my guest marcel hers fromtaliter beste capital is a podcast about how people make money and puttheir capital to work in to do start up: founders angel investors, venturecapitalists, crypton stock traders, real asite investors and leaders intechnology. Today, i'm extra excited to have my guest on the show, because heis the ceo and co founder of a company that i actually did. An angelinvestment in via the angel is platform in particular brandon hill. He was thelead of that investment in this company. It's called taliter, i totallybutchered the pronunciation of this company. In fact, in my head, i've beencalling it till eter for many many months ever since i invested in it. Inever heard it pronounced before. This is the first time i get corrected it'sto leter marcel is the ceo co founder, as i said, and not only am i excitedbecause i'm an angel investor in this company, but i'm also excited becausethis is some very cool technology that i think has some massive ramificationsfor the future. So the leter is accelerating the democratization ofcomputer vision. Ital, hear mysel explain their entry to market isactually in the groceries retail sector and they're, using computer vision toscan products, in particular fruit and veg. So fruit and vegetables, which, asyou might know, often doesn't have a bar code or in order to get a part, goton it. They have to wrap it in plastic, which of course, you know, increasescost and it's not great for the environment, so their first product inmarket right now is actually a checkout, a scanner for fruit and vegetables. Soa person come up like you normally do when you go to the grocery store. Youput your apple down your bananas, your grapes, your water, melons, whatever itis it scans, it identifies it prices it in a way you go so that's alreadyreplacing you know the manual process you might have had to previously dowhat you type in the number for the product, and obviously that slowsthings down. That's just scratching the surface of the potential here, but theyare very much rolling out initially using this hardware product with asoftware back into the market there in hundreds of grocery stores around theworld. As you hear marshal talk about, and it's proving very, very popular-and i suspect, certainly for the short term future- that's where the growth isgoing to come from, but marcel is very cognizant of where this is going. Hehas a vision for the potential of this technology because, as you can imagine,with computer vision, you can start identifying anything in the world, sothe potential is huge for collecting data for making things more efficientmen to talk about one of the next things, they're ready working on, whichis counting the number of human beings waiting in line, so they can open upmore check outs as that line gets. You know past a certain point to makethings you know more efficient, but a customer service, and so on. So againthis scratching the surface. This is going to be amazing where it could takeus, but right now it's just about rolling it out to his many grocerystores as possible. He does actually ask a few questions about. You knowwhat the future might look like and, of course it's i think of this, but it's aright great point. There probably won't be a physical check out, and thisprobably won't be a hardware solution. At some point it will just be softwaresitting on your phone and your phone obviously has a camera, so it canalready be used as a scanner to identify objects in the world. You're,probably aware of the amazon ghost stores that exist right now, where youcan just walk in the store. You take things off the shelves and you put itin your back and you exit in aran math. He charges you. That system is a littlebit more clunky, as they have cameras all over the actual space to see whatyou're doing. I could imagine a world where you just have an app you open itup on your phone and you just scan each item by hand as you put it into yourbasket in the way you go. In fact, that's apparently happening alreadywith some stories around the world, since obviously there's bar codes, butthis is only going to become more effective, more efficient as computervision gets better and leader is very much at the forefront of that andfocusing on the software side. This is also well worth listening to us, aninterview, because i do ask marcel to explain the origin of this, becauseit's a hardware challenge with software as well, so they had to create a youknow, a very early baiter prototype version tested out. He talked aboutsome of the mistakes it made in key demonstrations. They have to do infront of executive, so that was a bit and even in front of televisionactually that alive crew, where it didn't work very well, it's scanned anitem and didn't have the right identification, so some very coolstories from the start up journey, but it is actually well and truly in marketnow, and you know it's a functioning product and that's very much why idecided to invest a they have traction. It's working huge chains around theworld are using them grocery stores, but also where this technology is going.I could see it really branch out into some amazing places. So that's what gotme excited about. That's why i decided to do an angel investment and that'swhy i'm so grateful that we could have a chat with marcel to talk about thistechnology, this company and where computer vision is taking us. Okay, ifyou have not done so already, please subscribe to this podcast, it's calledvested capital. You can grab all the lays interviews as i release them. Justlook: provest aa capital in your phone...

...aft, where listen to podcast. Maybe youhave it open right now, hit the subscribe, but on the plus, but on thefollow button. I'd love to have you as a subscriber and also the one sponsor ialways mentioned in this show is my own company in box oncome, we provide emailassistants who will step in and take over replying and managing your emailand building a system to take you out of the loop. So you don't have tocomplete processes and treat your email like it to do list each day so designedto free you up, give you that hour or two or three or four hours that youcurrently spend an email. You get this person to work with directly who willmanage it and reply to your messages, for you just go to in box downcome formore in so about that. Okay, now, here is the fantastic interview with marcelenjoy hello myself. Thank you for joining me today, yeah nice, to makeyou and thanks for having me, really excited to get this going me too. Ivery excited because i love tillet, er and and what you guys, i'm not sure.I'm saying that right, i actually never realized. There might be a differentway to say that, but i love what your company does, especially because it'ssort of cutting edge technology. So for everyone who doesn't know what thebackground stories you want to tell us, what exactly is your company? What doesit do and what you know how far along, are you with the development of it sureso toledo's, like our vision, is really about like the maceta computer vision.This is where we initially started out and talk a little bit about the story,like holders all came about and why we believe it is sort portant for society,and so you know, computer vision has been really transformative for allkinds of industries. Sit like you, mentioning, like hell of retailmanufacturing like everything from autonomous cast to even autonomousstores for like what we're seeing with amazon, for example. With you know,these amazon goal stores popping up all over the world, but we realized veryearly on that. There are no commercial product availed that i allow this kindof computer vision, identification things to happen or, like the theydon't allow this out of the box, and you know something that you just plugin in the wall and it starts working, and that is essentially what we wantedto do right and if we went back now the time around, like four years ago, thecattles for me and my co founders was, you know a une. We had these subjectswhere we identified cancer cells or ma i skins and using computer division,and that's the first time i really got into this whole idea of you knowunderstanding how machine learning and computer division could really changeand transform society come back to that point, but we realize very early onthat unless you have this principle of making compute division accessible tothe world you need to. In order to do that, you need to create easy to useproducts, and you all like these examples are just mentioned, such asautonomous cars and autem stores. All of them are not self explanatory. Itlike, if you have to die in into this, unless you have like a computer sciencedegree, or you know, like you, studied engineering, there's literally no wayfor you right now to get this off the ground and that's exactly what wewanted to do right and our first commercial use case for this has been.You know, fresh produce, idification. I think this is what everyone knows usright now. Fresh produce is what we're doing, and it comes back to this wholeidea of using compete, division really to change the way people shop right now.So, for example, with you know, when we start with fresh podies when you go tointo a supermarket the first thing that you see is this huge variety of largeitems of you know fresh bodies, all of them look very different and the allthey prize very differently right. So it doesn't. It depends if you're in theus or if you are in europe all these items, you know, look different pricedifferent and you know like when, once you start your shopping journey, youput them in your basket on your trolley and you continue shopping. You knoweighty percent of all the items in supermarkets right now have barots. Soit's easy for us to identify those just by using the existing scanningtechnology. That's been around for like over forty years, but where you seepoems with a like items that don't have barcodes such as fresh produce rightand you know when you go through the store. First things, as i said, likeyou, you're getting fresh produce, but then you're getting other items thathave bark od. You know like an once. You continue your whole shoppingjourney. You go over to a check out and really you don't really. As as acustomer, you know, all of us are used to self service check out right, likeeveryone knows how to use them. You know you just skim the item, so you putthem over the skin and put them in your back. That's easy, but as soon as youcome to the point where you have to do this with items that donat backwards,you and real problems right, you're struggling because you don't reallyknow like what kind of apports you selected earlier right. You don't knowif there were red red, delicious rogala or anything like that, so you revert towhat you think is is most likely the cheapest. You know this is at least theproblem that we are seeing you a lot an...

...when people just say. Well, i don'tknow like the kind of brave apport you know it's definitely not that apple,because this is eight dollars, ninety nine to kill, and then you got like thered delicious, which may be special for one dollar and ninety nine. So there'sthis massive discrepancy between those different but similar looking items andthen obviously is a massive problem for retailers. You know like this wholeinventory management is something that they're really struggling with and youknow like you can even take this to an extreme. Sometimes we go like to yourlocal cause or who worse on you as to your crocus and balmat, you see, youknow ginger, for example, costing forty nine dollars a pound or like a kiloright and then you have those brown, onions or red onions. That cost may beforty nine cents a pound right. So there's this massive discrepancy, buteven though they were completely different right, but there's no way oflike telling this apart right now from the supermarket point of view right,like you can't just i mean unless you have someone standing behind everytransaction that anyone is doing, which is, you know, not really feasible, thenthis is really a personal thing. You know that hits home every time plasticright like what we're seeing a lot of fresh polices, wrapped and plastic, andwhy is that right? Yes, it's to extend self life to a certain extent, but whatwe're really seeing problems with is when retail is doing this really justto put backlet on him, and that reason for that barcode is the same way oflike eighty percent of all items have backords is really to speed that up,and you know we think this is unfeasible. You know like we shouldn'tbe suffering just because you know like it is this speed and also experiencedfactor for the customer, so this is, you know like essentially that journeythat just took you on that was four years ago. The first time you know likeme, my personally, i'm from germany. You know if you don't really have sosort is check outs there, but here in australia you got probably sixtyseventy percent of all check, outs or self service, and you know, likefiguring all of this out like on the goal, was such a nightman. We side likeyes, but you know, let's put something in here. If you think about computervision, transforming the world may as well use it to a product that anyonewill be using at any given time right- and you know like we developedessentially in machine learning, compute division, algorithms and we candive later into the technology and how it works and white is so different tothe normal approaches that we see out in the field. But you know that was forus all right. Let's put this in it's so self, explaining right, like it's, notbread. Now for anyone right, it's maybe not the thing. When you ask someone hadhow could you change my shopping journey majority of people wouldn't sayjust like identify fresh potes at the majority of people wouldn't even knowthey're like yeah. It's annoying, but it's not like you know hey. This islike my number one pay point, but you know it really speeds up the processand like from caston experience. Point of view is great yeah. I have to admitwhen i first heard about you guys it was. I was brandon hill actually andwhen he was one of your investors and i had an opportunity to be part of hissyndicate lead and make a small investment in you guys, it got meexcited because i thought: okay, like you just described it's a very obviousefficiency problem, simple! It's a great first go to market solution to acommon problem that i can see you guys and you are getting traction with, butthen my mind went, you know. Where does this go? Where does identifying objectswith computers lead to, and obviously i thought about cars you know the tom wasdriving now there is a sense of identifying what's around the car usingcomputer vision to figure out, but i feel like you, you in particularmarcels a ceo. You must be thinking of the vision of this company. You know,whereas computer vision going to take you without maybe giving away all yoursecrets, i would love to know what what what is i mean i feel, like you, don'tfeel limited by just going after identifying fruit and benches. You seethis becoming a much bigger potential market so where, where do you see yougoing yeah and eperson get you? I mean you know like the first four years ofour journey. Now people refer to us as the fresh beggi guys. You know i ratherthan actually technology company that we are, which is fine. I think i'd liketo, like you know, like a page out of pts playbook, where you sayingbasically, you know, go after the niche market, dominate that niche marketright and then expand expand from there right and that's exactly like ourplaybook rights like we want to dominate fresh bodies. We believe thisis a winataree market, but it's just the beginning and to reason why we pickfresh produce, i think maybe in hindsight we would have picked it justbecause you know, like the other struggles, that you're facing along theway, but you know like now: we really embedded took a long time to get thisoff the ground, but the vision is, as i said, democratizing come, try, division.You know like it's going to take forty fifty years to get there, and you knowour mission statement is to sad, accelerate computer vision, and thenyou know like by creating easy to use products o. So essentially, what we didwith fresh bodies was product...

...identification, very specific productidentification right, but this is not necessarily where i see you know like.I think that two ways of going about this is either you going really deepinto certain areas in ich areas, and you can do this any time, but you cando this with fresh bodies. The next one may be bakery items the next one. Maybeyou know like even going out of this. Maybe you know like in a manufacturingidentifying hard heads- or you know like these kind of things, and you cando this or you can go. You know broad and that's essentially, where i seeteleda going really facilitating computer vision rather than you know,doing all the heavy lifting every time ourselves save. For example, the freshbodies in all the heavy lifting was four years of you, know pat nerd andand unique algorithms that we developed for that particular use case, which iwould say so far set us apart from the competition. But this is not the bestuse of de mocatta computer vision, because, if you're doing this for eachone of those, you know it's going to take you a long long time. It's goingto probably take us four hundred years to do that rather than forty years. Soyou know like, for example, this fresh produce has been like our first product,but you know we already have like a second product where we had essentiallyidentifying people queuing up in stores and then feeding that back to thecashiers to open more check out. You know so this is like another. You knowlike where this is going, where this, like development of you, knowidentifying people in the store, because he can use existinginfrastructure and open source software on certain things. You know it's mucheasier than diving, deep and thus, as a company, i really see us. You know likegoing day broad, offering this facilitating this. You know by aplatforms or really by a broad product, but people can just pluck them in andpotentially even have the chance like to develop their own algorithms, okay,interesting so very much in i guess. Retail space at the moment is where youguys are playing in which, which makes a lot of sense. Would you mind justupdating us, as we record this, where how i m going to say this right is tolet her not tillet or to lead her. How far along? Are you like what like levelof presents? Do you currently have in the market place yeah? So we life rightare thing in all about fifty eight sixty stores over hundreds, hundreds ofsystems deployed, and it's really all across the globe, and this comes backto the winner- takes it all market. We started in europe and in australia,australia. Is that perfect testing ground? It really is hard to correct,though, because you got basically three retailers controlling australia, likeyou know, with sixteen sixty five percent market share. So, where youknow the europe an us, you know like you got those big players, such as war,might crove, but small is relative terms of australia, but you got thoselike small champions right that i have like three hundred four stores: amassive footprints. You know tens of billions of dollars in revenue, butit's very easy once you have convinced not very easy, but once you convincelike those large, you know supermarket chains and that become advocates. Thisis then, when you like, have to expand like out of australia and and that'swhat we did right so like we have got our presents now in in australia in theus, and we going into south america, central america, europe as well- andyou will see this- these massive roll ots happening now like over the nextsix to twelve months, where we really see our technology and we'll see ourtechnology and hundreds and thousands of stores. But you know like it tookthat long. You know like to really get that confidence yeah. I can imagine andi'd love to know the early days actually before i ask you about the thestarting point: i'm curious, what the what's the business model with this andi'm assuming it will evolve over time, but you know: do you? Do you rent aunit like? Is it like a box that you basically put inside a grocery storeand they pay a rental feel like how does it work yeah? It's a bit morecomplicated than this, as we have quite a large product offering, but this isyou know like if you, if you look at supermarkets, not many supermarketslook the same as as say like a coat of wars. They all of very they have likesmall, slight changes which makes it hardest to scale, but nevertheless,like we found, you know like o five six product variations and that reallyscale globally. But essentially, you know like this. The that true things onis the hardware box, which is essentially, i can edge device you alllike, which does all the predictions on the device itself, rather than sendingit to the cloud and back this is, you know, like you, retell us just pay forthis on of the rights like the pay that hardway and then yearly sofersubscription, lisence, that's the business model, and then we've got alsolike fully contained systems that basically like the function as checkoutand those systems you know like they have a scale system in there. They gota pall. The point of cells, but also like our underlying technology,powering the whole thing, and this is the same business model, so you pay forthe system and and then for the youth...

...subscriptions. Okay got it, so it'ssort of like a stand: loan scanner or a complete check out. Do you mind if i goback in time marcel and, like i think about this, and i can imagineentrepreneurs listening to this building something physical andtechnically advanced is daunting to begin with- and it sounds like yourbackground is more medical. If that's right, you are studying you no more inthat space of biomedical, maybe early on so take us back to when you firsthad this idea and you decided to actually go for it. Did you think, okay,i'm going to raise ten million dollars and mentor capital just to build aprototype and then we'll go from there like? How do you start something as bigas this yeah? I mean my back mont. My initial background is actuallymechanical engineering, so this is where the whole like, like thedesigning- and you know, like all boxes- and you know like michael controllingreally comes from- i mean initially, you know like if i take it back nowlike say four years: yeah for four and a half years. We didn't really knowanything about like raising funding or you know like how much do you actuallyneed it? Essentially, when you start out, i mean this is where you start out,but like you have no idea, you don't know if you need like ten milliondollars, you think about like hey. Maybe i need one hundred thousanddollars right and i'm going to scale this up all around the world. This is your that at night it like when youfirst stay out- and this is what we did. You know like rest- a little bit ofmoney from you're, not really just prints of family right. We didn't knowanyone and was super hard like to that was again four years ago, i would say,like the startup seem look very different. He and sidney very differentright, like even like angel investors. You know, as soon as you mentioned theword hard ware, everyone's just running for the hills. You know no one. No one really wanted to investanything like hardly related. Then you have that next point. Where you sayit's not just hardware, it's also going to be in retail and everyone's likerita, oh no. Why would we ever invest in retail? You know like if you go to asupermarket, nothing has changed in the last ten years right, some of them evensay you know certain retails are still using the same technology at the useforty years ago, but it is time it's the same with every industry. At onestage, you know like the need to overhaul their systems in order. Youknow especially like i think, covin showed this really, where you see andall of the sudden re tellers need to step up the game if they don't want tolose to amazon or like even to you know like the guerillas of the world, youknow do these online deliveries. If they don't want to lose, they have toyou know, step up the game, i mean we never thought about even raisingbenchara. We thought you know like hey. Maybe you know we just need a littlebit of money here and there and then scale this up globally. But, as youmention you know like hard were, is a reason why it had with it's calledhardware it's hard, but and it's not as easy to scale a software and yeah like i mean a long. The way welearned all these lessons and we're like all right. I think we need someventure capital yer right. But again you know like coming back to hardware.It is this competitive mode. You know that you have really well when peoplelook at you and their life shit they're bringing their heart resolution intheir own. You know software system on their their own os and and it's veryhard to replace, and then you go like to retell us that have those long salecycles. You know like of one two years until they buy something, but then theydon't change it for the next five to ten years right. So once you're in it'svery hard to get out- and you see this with all these legacy systemseverywhere in supermarkets all around the world, but the adventure capitalwas until i would say like two years ago, a venture captive wasn't really onthe cards. As much okay, well you an we have my question. The other half is:what did you build first, and how much did it end up costing to to createsomething? I mean we all when first started tolead up. We all still used to work our day day, jobs. You know, obviously notas efficient anymore as we used to, but this is how we created it right, likereally with our hard earned money everything that we had like i put youknow everyone put all the savings in it and then you know we got money fromfrom our parents and also like the first. You know, friends that believedin what we could be doing, and this is how we build it. You know like from theharder aspect, and obviously you know like we need more money. The morepeople we hire. The more problems is the thing. If you hire more people, youalso like causing more problems because more have it. So we need to raise moreand more money, and we did this like in a rolling session rather than you know,saying all right, we're raising our five million dollars. Please all investme. You know race a lot of like safe agreements by our safe agreements. Youknow from institutional investors such as universities, but not really fromdensher capital until last year in october. This is the the first timethat we really raised. You know five five and a half million dollars and aspart of the venture around, but before everything was rolling, so we alwaysjust raised moneyy when we needed it,...

...you know, and the frequency just backbecame like you know it became closer and closer, but to go back to theprototype like was it regardless of how much it costs? I'm imagining it's youbeing a hardware guy. You have that skill set. Were you literally in agarage putting together components and then marrying that with software likehow did the? How did you physically create this in the first place? Yeah,so i would say that the first poor type basically looked like an ikea lamp andwe had a webcam mounted on top of it. You know like and kit y, not like. Iwas collecting data for three four weeks. You know like we bought so manyprudent vegetables. We made apple pie, for i think four weeks straight. You know- and this is how we collectedtoday, that this is how we had all initial prototype and the next one iactually welded this out of steel. I don't think we have that torn tapanymore, but i think the whole weight of the poor time is like twenty fivekillers. I kite was like made out of steel like a physical steel, and we hadlike a haricane at touched it, but really just like anything to get by. Iwe didn't have fancy through the printing technology or anything likethat, so we just try it to somehow make it look more commercial which, and thenwe invested in the like three deprend technology. You know like to really imean this is the thing right like with startup cost by they're, saying thisnew generation doesn't need as much up front money as they used to right,because you've got three d prenty technology available. You got softwarepackages, you know like back, then we were able to use. You know like opensource software, and you know that's that's how we survived back then. Youknow like, without that you know initial capital outlay of like one twomillion dollars. Okay, so just so i understand it in my head. You could geta web cam a light, some open source software that does the basically theinterpretation of what the web cam is seeing an attempts to identify theobject, and then you try and turn that into something that is commerciallyviable like it looks like something people be willing to put into theirgrocery store the software functions without bugs you know you an you, don'thave to go in there and fix it, because when you're rolling it out to awalworth or calls or a kroger or whatever an ald you, i can imagine thefirst time you were probably sitting there watching it carefully. Pleasedon't break, please don't break, but you know to be in as many stores as youguys are right now you have to trust that this thing is this going to beworking day after day minute after minute, you know scanning translatingeverything work. So how long did it take to make it to the point where youfelt it was commercially viable? Has so many great stories? Just just do you know like thinking aboutthat timeline? You know it took us really two years to get, i would say,like one and a half years, probably like to get it to a scalable point. Sothe initial problems that many companies are facing with computervision is as soon as the lighting. Now yes changes or like the environmentchanges. The whole system just predicts nonsense right and we had this removented a first or i remember, also collecting data for a couple of weeks,and you know like the bad channel seven, which is this tv show you know like inthe. I think it was sixty minutes some. I can't really remember that theprogram what it was called, but they rocked up with you, know like a wholefilm crew and everyone was expecting the system to work. But for some reasonyou know like in this is like what you discover along the way. For some reason,our system just wouldn't perform at certain times. You know- and i was justlike there was too much sun in the store and our data was collected atnight time. These were the initial struggles that we had so we go thereand you know, like the whole film crew, everything is going well and i'm justlike i'm literally like i'm sweating right, it's like i put down a plancomes up as a water meter, these kind of things right and but butit was good right like it's, this initial learning all right. Howvulnerable are these computer vision, algorithms, and what do we need to doin order to overcome those initial promise that we faced? And that'sthat's what we did right like, and we slowly developed it to that? Like thatsofter that you see now i do worse. You know like now, like i'm, not voye, youknow like you can go in there right now and i know maybe ninety five percent ofthe times that system will be ripe. I know that right and you know we'redoing hundreds of thousands of transactions every month, and you knowthis is this is good now but, like i would say, like two and a half threeyears ago, we still had like this initial problems, and this is justcomplete vision. Product and it has developed a lot- you know like thesepeople- ned algorithms, for example- that you see that identified people.Those things were really shaky a couple of years ago and now like they havefinally arrived at the point where, where you can deploy them without without too many false predictionsright yeah and you trigger a thouht...

...when you were talking about thecounting of people with with computer vision and then you're moving in thatdirection already, i understand the reason why you just are simple. Youknow we need more staff to man the check out or just simple as that ormaybe even calculating retail space and how to distribute food, and you know,place products around the store. Where does this become a a privacy problem? Because i know youprobably had people talk about that and obviously in countries like china,they're scanning everybody faces, you know they use their faces to log intothings without even needing another human being there, countries likeaustralia, canada, america, it's a little bit more cautious on the side ofprivacy. So have you bumped into any challenges with this idea that whatyou're doing might be potential privacy? So people don't want to be counted,don't want to be scanned as there been anything along those lines. Yeah i meanthis gdp compliance. You know like we take this very seriously and it'scoming back to this whole idea of having edge devices edge devices rightnow. You know they don't send that data to the cloud. No video streams, it'sreally just sending metadata right. So what the people had, for example, youknow like one of those retailers will see is essentially all right now, liketwo people are lining up, but they don't have, they can't see who islining up or what they say is all right. We had full capacity now, please openand lovers check out or another counter, or even he's the real deal about likethis people counting and c detection. It is really it gives an access. Twentyfour seven of like what kind of changes you know like in their stall out, forexample, what kind of effect they will have right and they can track thisevery day. Right so, like they're changing one thing now, like a weeklater, they can assess all the data and it's like well, we moved one check outover over here and all of the sudden you know we were able to reduce ourcheck out time by ten seconds per person, which is massive right, and ifyou think about this, this is normally what consulting firms are getting paidfor in all like what i ka pm, g or p wc, what they're getting paid for you knowlike sending people in there and making sure that those statistics come back tothe retailers now, essentially, what computer vision allows you to do isgiving them access to this kind of date at twenty four, seven right withoutreaching any of these privacy. You know problems that you just mentioned,because i believe it is a real problem right like if i was able to identifyevery time you go into a store right. I mean yes, there's that's how the sidethere's the flip side of the of the coin, where you could say well, i couldnow target this per particular person with advertising. You know like withtit requirements and all of that right, but we all know australian and like thewestern world in general, ride it's not really seen as an advantage to customer,rather a disadvantage right. Finally enough, you know like if everyone isokay, you know for private for facebook to collect all your information rightwell like for zere when you're talking to it right, like everyone is pine withthat, but as soon as it comes to all right now, like you know, we may targetyou when you go to a supermarket, to you know, make your will to let thesteels, but again like we have to be compliant with. You know, whatever kindof regulations we come under, and i still believe you know it is great theway we're doing it right now, but i see like a massive. You know change,probably in society in the next couple of years, but people are okay with thatright. If i mean you know, if i go in the store, i don't drink normal milk, ijust drink, i'm a mill, gride it'd, be good it'd, be good. To show me okay,where is that armor milk right and right now, like you're, doingthis through apps, but i believe computer vision might be. You know likethe better solution that in the future yeah, i can imagine like all the side.Science fiction movies, i've seen where an ad pops up where you're shopping andit's you know the hologram telling you something but, like you said it couldbe a search base tool as well you're wondering where this item is in thestore and they already have data about you. You want milk, when you say milk,it's almond, milk, its in ile, four etc. Interest thing. Would you my taking hisback, though, to the point where you move past that early stage, the appleis no longer scanned as a water melland, it's actually working you'recomfortable with it rolling out to many many stores. How do you then expand andscale given? This is up, like you said it's a hardware solution. It's aphysical product, even though i think it's really a software problem.Ultimately, you still have this physical device. You have to place instores and you've expanded globally from sydney which is obviously far awayfrom a lot of these places in europe. How did you? How did you go from thatworking first version to to convincing these big chains to actually give you achance, and you know, prove it works for them yeah. One thing to understand, i believearound two thousand and eleven, the first fresh bodies, idification systemspopped up around the world and you know like bag back then i believe i'd be andwas involved in this. That then got so...

...to toshiba. But what happened was backthen? Obviously, you didn't have that computational power, you know like you,may have to algorithms, but you didn't have the computation of power in orderto process what those algorithms are giving you right, and essentially a lotof retailers put a lot of money into this kind of technology back in the twothousand and ten two thousand and eleven right war when they ended upbeing happening, was that the majority of retails got burnt by it and burnedin a bad way that you know like they had all these capes cost of machinealgorithms or machine learning. Algorithms that you know didn't, haveany relevance for the retailer back. Just couldn't use it right, it wouldnever work. Those initial promise. I talked about earlier, that's exactlywhat they were facing right and all of the sudden it was to all pm, andeverything came up, as you know, is a steak, these kind of things and for usinitially. What we did is we built up a team in germany, and that was superimportant. You know like to service or a biggest clients, you knowand essentially how you commenced those big clients and comes back to thiswhole thing about the principle of you know having easy to use products.Essentially what we did is you know like we took our systems and took thisto the headquarter right and invited hundreds of executives right and maybeten fifteen ended up coming right to the store and we demoded in front ofthem right. We gave them basically the opportunity to themar everything to totheir own folks at avrone super interested that if this works, yes, wewill put it in everywhere, right and but yeah, obviously a lot of scatters m,and you know once that were able to show it to their superior to theirexecutives. All of a sudden, this got really momentum right and that's that'show we did it in europe and you in australia. We actually used themomentum that we created in europe to bring it back to australia, so thefirst doors were in europe that in australia it, but then obviouslyaustralia, is this small puppy syndrome. Right, like you, don't want to miss tosomeone, especially in retails, you know innovative, or you know likeshying these new things so like you want to do that here as well, and weended up. You know like having really good products and then like the us, so we always knew in order to crack the us.You need people that have a lot of existing relationships. You needbasically gray hair kind of sales, people kind of people that that donethis already, you know like. Maybe it was twenty thirty years ago withsomething unique you know for us. In our case, it was someone that you knowwas one of the co founders of a scale management software company. So he haddone that. You know twenty thirty years ago so to all these massive retailersout of the garage right. So essentially i messaged him. You know like we hadsome very good talks and i was like you know what you did that to twentythirty years ago. Can you do it again? Can you do it, for you know what we areofferee? He said all right, i'm willing to give it a shot, and this was reallynow, like i mean real life. Is you know, albert sons, you know is like one ofthe largest recolor in the us. They are a couple of other ones that areunfortunately can't mention right now that you will see where those systemswill pop up in the next. Probably two three months- and you know like you,don't get access to these kind of customers. If you don't have someone onthe ground that has done these kind of things before you know, i meanessentially some of them, like a multi million dollar deals right. You can'tjust like walk into the executive rooms like please buy this. You know, andplease by for fifty starts, it's not it's not going to work unless you havethose relationships when you come into canada. When can i actually experienceone of these myself we're trying we're trying, hopefully soon, hopefully, bythe end of this year, like we, we got some, you know like you got the so besthe la blas. We got some some of them already interested and it's just therefast now pushing them over the line to try these kind of technology. Becauseof this it is mind blowing when it's working, you know, unfortunately, youleft australia now like otherwise you you would have the best experience hertrue. So take us far with the future, then i know you already kind of mappedout some of the ideas with where computer vision might go sort of overforty years. But what with toleta in the next sort of five to ten years? Isit just a case of like you said it's like a you know, winter take all kindof scenario. Is it just a case of trying to get into as many grocerystores around the world and just become the de facto tool for scanning,whatever needs scanning in a retailer, a grocery retailer, and also what isthe challenge? There is it's simply the relationships and the slow sort ofconvincing sales cycle you have to go through, or is it really about buildinga team in every single country, and that also takes a lot of time? Yeah.There's a lot to un packie, it is yeah. First of all, you need a team and youjust need that team. You know like to...

...really give those retailers theconfidence in you right. I mean they heard it all the four. You knowsoftware companies that try to scale like r m, if it's israel or australiaor any other country, it is tough, especially for us. It's really crucialto keep those relationships, but also build up on these relationships that weare having with those retailers to you know, get more of these new nextgeneration products exam. What i'm seeing right now is, you know likewe're doing fresh pods recognition on check outs, which is great right, but ialso believe that the next horizon there might not be any more check outs.You know in ten years time there might not be any right or you will see them,maybe similar to like patrol cars in twenty years. He i like everything, isgoing to be electric and that's probably like how you see check out aswell. So obviously we don't want to put all our money, all our innovation intosomething that might become redundant. So what you will see a lot from us is,we will be going into morbi and we already you know doing a couple ofthings there with morbid. Where you know you just use your phone in orderto identify. You know what kind of item it is pairing. This, then, with the waythat is measured somewhere as formal legislation. One of you how you do thisthat there's another story, but i believe you know like us. We will golike into mobile. We will go into more areas where we don't necessarily needintegration. Integration is always key. Ri integrating into a retailer systemtakes a long time. Yes, i gives you that competitive mode be just becauseyou know others have to do the same thing again right, which timelinesometimes can vary between six twelve months, but i believe the future willbe not just an autonomous stores, the ones that you see them as on go, butyou will also see like a hybrid version where people use them, other phones or,potentially even you know their next gadgets. You know right now. I thinkeveryone's got like these smart watchers. You know, maybe it's smartglasses, smart contact lenses, whatever it's it's going to be, but but usingthis, and really that transform this whole company more and more into asoftware company. Right now you know, like i would say, like from a rrediisti e. Eighty percent of this goes back to hardware twenty percent tosoftware right, but this will change now. The next couple of years will makemore and more money from not just recurring revenue, but also offeringsofter packages without hardware involvement. You know like i'm from acap, pon of you. That's that's essentially, where we see this wholeindustry is going. You will see a lot from us that will support mobile phonesand not just more but thorns also hand held scanners and de sorts rightcorrectly. If i'm wrong benefit. If i'm reading what you're saying it would belike, i would go to the grocery store, i put everything i want to buy into mymy bag. I bring it to an area whether i could then i could even do this as i'mshopping. I guess i have my phone out. I take an item off the shelf. I just usethe camera to look at it. It adds it to an app which is the at for that grocerystore chain. I just put it straight in my bag. It's added to my my list ofthings i'm buying in the app. I just do that as i'm shopping, and then i justclick by kind of like i would do it with you know. Online shopping set themdoing it in the real world, and this like the technology. You won't need barcodes because the computer vision would just know this is a product i couldjust read whatever the boxes and even the writing on the box, and it couldidentify any kind of object or packaging whatsoever. Is that kind ofwhat you're painting as a picture of the potential future? So this isalready happening right now. It's happening with park cods, so you know,like the stores that i was mentioning, save, for example, with owers. You knowlike we are think life and you not thirty, thirty, thirty, five stores,where you do this exact thing that you just mentioned you know, like you, takea photo of the of the bark cord. It kanzi already doesn't take a follow ofthe item and recognize the either. But just does the bark cord and now, likethe part it doesn't. Work, is the fresh bodys right. This is why we have thosewhole checkout systems where you place the item down and then it just pops upwith the back cord as well right and but i'm seeing you know going forward.You will see less and less of like these checkout systems, and you willsee more and more of mobile recognition. You know like where you potentiallydon't even need those check out systems. You know like because you do everything,as you just said, on the air, okay yeah. That makes sense like we're gettingused to doing it with qr codes to look at the menu with covin, and it's likeeveryone sort of expects, the on the phone to be the interface or everythingor the watch or or whatever or, like you said, a portable pan device thatyou could also use. If you don't have a phone in terms of growth of the company,i'm really asking this to, as you know, a small minority finality investor andwhat you're doing what is the timeline for all of this, like i can see whatyou know as long as you remain excited marcel individually, you personallyyou're going to be here for a long time growing this company, but w. Where doyou like? How does a company like yours...

...grow over the the next two for tenyears, because it is hardware, so it is a bit slower. It is a slower salescycle. Like you said this may be a transition period to as you move awayfrom hardware to more phone and app bay solutions. You, obviously you need tokeep raising funds to keep building the team. Every time you hire a e developer.You said you, you know you need to have more money to pay them, and i ask thisbecause i'm a software web kind of guy and i kind of understand how that we'reexpecting the hardware world i feel like you, have to be really carefulwith your cap. Bex your expenditure, you, you know you're, raising funds asyou go along, you can't just boot, strap it's very difficult to use themoney you're making to keep rowing. So how do you take the next sort of threefour five? Ten years in scaling and manager, everything manage everythingyou're, the ceo, so y? U y, i'm sure, you're thinking about this every singleday, yeah! It's a good question. You know for us right now. We basicallybootstrapped, i would say you know, dodett in a sense, with a little bit ofcaptal until last year middle of last year, and now we really have taken somefuel from venture capitalist in order to to really go after those, you knowlarge markets, but it's like. We always said that if we just want to do freshbodies, we probably wouldn't have to raise any capital right. It's just likeyou become capital efficient. You know you got your subscription fees, you'reselling the hardware margin you know, so this is all working well, but inorder to take on really the world and democedes computer vision, you willneed a lot of funding and the reason why you need a lot of funding is to runexperiments. So i'm a huge friend, i'm a product guy right, like i love likerunning experiments and just finding out, you know like after a very shorttime like is this working or its is not working right, but you need thatinternal conviction as well. As i think this is super important right. We areinternally we were convicted that computer division is going to be thefuture, but like if you look at fourth industrial revolution, compute divisionis a massive part of this right like i, i will transform society. We know thatright, so conviction is. Nothing is missing there just like how do you getthere and all er to run those experiments? We will need access tomoney, but if that means you know like more venture capitalists or you know atone stage, taking the company public and then really you know. I love thatfrom jeff besos, when when you took amazon public and an he said like yeahthe stock market for some reason, like all our internal numbers went up right,but the stock market, you know, like all our numbers went down, but but weknew like inside amazon. You know like we had something really great here, andyou know i believe you know like if you go public or if we become stay private,for you know a couple of more years. Nevertheless, like the future of thecompany i think is secured. We just really need to execute a long. The waydoing more of those experiments and- and this is you know, like thecompanies day in a we- are product focus. We are very product drivencompany in order to figure out like the right, the right things in the rightproducts along the way you just need capital, but right now we are not. Youknow like in order to keep growing. You know like the fifty five people now i,but i hope, like in any year's time. You know like that. We we double ortriple that and just because there's so much opportunity out there rightcomputer vision, if you think about this everything that, right now that weare seeing you know, some of this can be taken care of by machines and somuch better. It's so much more convenient and you know more efficientfor us humans. No, i love it. I love the vision. I love the future focushere and the product focus to maybe like kind of wrapping up here, a littlebit marcelle, i'm curious, you know being a product guy. You must feel likeyou want to have your hands involved with every experiment, but what reallyis a day in the life of marcel as the ceo of taliter? Are you still playingwith product or you more about hiring and firing people with your day to daykind of role or building relationships? What do you do every day? Yeah, i'mstill like massively involved in product. You know i will never givethat up. I don't gates like even like until the last day he wasn't everyproduct with you meeting at the company ever had. So i seemyself the same way there. I do a lot of things in terms of hiring. Having isreally what i'm focusing on now and it's about not the people that you'rehiring tomorrow, but the people that you will be hiring in three months, sixmonths, twelve months right, so we have a great network from people you knowlike through films such as angel list. You know like where you have a lot ofindividual investors and everyone is willing to help. You know. I think thisis what i love about angels, but even like elinor ventures or flight foxman,she here from from australia, and they have a lot of people. All of them arewilling to help, and you know, potentially some of them could becomeyour next higher your next vpon, your next deposal, but so that's that's alot of what i'm doing and then, obviously you know keeping the lightson speaking to venture capitalist. We are in the process of you, know justramping up for csb, so you know i m spending a lot of time there andbuilding relationships. You know, obviously you know still the steward ofthe of the culture of the company...

...culture. I don't see that changing much,you know and then obviously you know thinking about tragedy, really notthinking about this short term strategy that, like the next year, i think thatthe company really got that, but the next three five ten years you know,like, i think, even masters, like gray at this. You know like pointing outlike how the world will look like in five hundred years time and slowlytaking it back right. Like how does it look like in one hundred years, fiftyyears, ten years? What do we have to do in order to move to needle and and ilike- i'm spending- you know like i'm spending my l life. Essentially, youknow like looking for the right kind of strategies might like, and none of themwill be perfect. You know there will be adjustments along the way, but i'm finewith that. No, i love it. I love it exciting, citing industry working andbeing a product guy. I must be so satisfying to see these things roll outand perform, and and then you get excited about the next duration and thenext experiment and you kind of websites we can send people to it andyou know dot you're hiring too, so any specific job openings. You want a highlight before we begin the call a data, so we're really looking for a head ofdata head of ai. I mean you can't have too many machine running engineers, andyou know you as always need to be super careful that they're not gettingsnatched up by you know like those big corporate, the tang companies- and theyjust have you know at least so much money at their disposal, and but youknow like from what we're seeing we got a lot of great talent and the reasonwhy we're getting that talent is because you know it is exciting. It isexciting what we're working on right. I mean we're talked about fresh produceidentification. You know everyone is using this every single day they gointo a store or like, even if you use online delivery right, like thoseonline delivery people, you know they're still using the same kind oftechnology like they still need to check out. They still need to use oursystems right so and to end right like if it goes more into direction ofonline or offline, a breaking morter, you know, anyways, like the technology,will always be there. Yeah i mean for us yea. No, please apply, we've gottons of open rules, but we would like to hire for but yeah engineers,software hardware and definitely day die and machine learning. Is that ontility? Do you have an external website? You use yeah, so it's on tilicum andthe two were pages wants to like to lead that ol come which is really aboutthis whole vision of democratizing country division, and then we've got tolead our retail come, which is you know the taylor to our retail customers, butyet just head on till you come and have a look at jobs. Okay, i include all thelinks from the show notes, yeah. I really agree with this idea of you know:working for a company like yours versus, say, yeah joining a fang, but he mightbe just trying to make advertising improve their click, the rats and getpeople to pay more attention to an ad, which is you know it's a job, but it'snot exactly the sense of fulfillment, improving the world and taking thingsto a better place. So i think it working for a company like likeyourself at this stage would be way more exciting. Are those jobs all likeremote nowadays, like? I know you guys, australia? Germany are big parts ofwhere you're at, but is it? Is it really a global, remote work force? Nowi mean it's not totally remote because you have to have the element- and yousee this- you know apple in orders, a lot of the employees back to the store,just because the we're seeing a lot of this is. You know like from acreativity level. It is sometimes really good to have those white boardsessions. You know like do. You have have involved to see. You know what ispossible, but we're getting there right now i mean wen sitting near in the lockdown, so we can't go in your office any time soon. You know it's probably goingto be another two months or something like that. We really want to grow. Thatdoesn't necessarily mean you know like it can't be outside of our headquarters.You know like i would love to high more people, especially like in the us. Youknow where we see a lot of this, but again it's probably like a base. Youknow, like we've, got a basin in rochester in the us in new york, butyou know like they is potentially now that will be hiring my people on thewest coast on the east coast. Definitely, okay, awesome! All right,myself will wrap it up. Is there an email address or twitter linkedinaccount? What do you prefer to give out for you personally if people did wantto get in touch for any reason, yeah i mean i could just give my personaladdress. I've got to you know like if i get too many melts on on bones. So onis masel. Dod hurts a toledan dole you, so you know, like feel free to justsend me message. If there's anything, i could do if you're looking for a job-or you know, potentially even like being a new investor, always appreciateit awesome, okay. Well, i appreciate the time i man i'd love to do this infive years time and see where everything is at. I think that'll be anamazing transition and what a story to share but yeah, i keep up the good workand i love i love hearing about it. So no doubt i'll hear through brandon aswell as things grow as he updates the syndicates oi'm. Looking forward tothat and yeah great to talk to you yeah. Thank you so much and thanks fivingthere you have it that very fun interview with marcel the co founderand ceo of taliter, a company. I've...

...done an angel investment, so i'm hopingwe'll become a unicorn, as we all hope, as angel investors, that the companieswe invest in will go. Big already has gone big in terms of a global flippinand all the stores are entering and all the partnerships they're opening up. Sosigns are good. You never really know. I think you can tell with marcel thesky, really is a limit with where this technology can take us and i'm excitedto see what new products and what new solutions come out of computer vision.It's an exciting world to be alive in right. Now, i'm going to wrap up theshow. I hope you enjoyed invested capital. This was episode numberthirteen if there is a friend or a family member or a colleague, or maybesomeone even a colfodder of your own. Who should hear this interview, maybeyou're doing a hardware software entry product to a new market. Maybe you knowusing new technology, it's ai computer vision, cryptocurrency whatever itmight be, but you want to hear a story from someone. Who's basically startedwith an idea turn it into a prototype and now rolling it out to stores aroundthe world. This might inspire you and or them so share with the investedcapital episode number thirteen. You can tell them to go to my website y, ar o t b. L o g go to the podcast tab, but also you can find us on spotify,google and apple podcast players on audible and amazon, where the podcastsections are pretty much anywhere. If you just type in vested capital or yaroy, a r o. You will find this show and then episode. Thirteen for theinterview with marcel hers. Okay, that's it from me. My name is yaro andi'll speak to you on the very next episode, thanks for listening, bye, bye.

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