How K Looks CEO Alexandre Abu-Jamra grew to $1M revenue and 50 customers in 2024.

guys klook.com dobr was launched back in 2021 2022 he broke 500,000 bucks of Revenue in 2023 cleaning a Brazilian financial data and selling it to Big firms like Captivate IQ and Bloomberg which many of you guys might actually you know listening might actually pay for directly some of that data is provided by these groups like KX he has specific OCR technology with his seven Engineers but then it's the human layer on top of that where they clean the data sort it filter it make sure and check for accuracy before they sell it off to the End Market uh that really is their secret lost 50% of his Revenue today and they'll do about a million dollars this year 50% of that is data as a service another 30% is pure services and then 20% is true software as a service completely bootstrap selling through two major resellers in Brazil That's neoway and TTR data uh where he takes a cut of the sales there if he goes direct he's selling for 300 to 400 bucks per month and has over 50 customers to date hey folks if we haven't met yet my name is Nathan ladka I launched and sold my first software company back in 2015 and went on on to write a book about it which you guys made a Wall Street Journal bestseller purchasing over 30,000 copies thank you so much for that after the book I launched this show and went went on to create founder path.com I raised a large fund to do non-dilutive deals with B2B software Founders so far we've invested in over 400 software Founders totaling $150 million here in 2024 we're doing three to four New Deals per week so if you're looking for Capital and don't want to give up Equity go sign up at founder path.com for free to get your offer all right let's jump into the interview hey folks my guest today is Alex abujamra he is a former m&a adviser in manufacturing CFO today he's a CEO and founder of K looks he graduated in business and administration sumacum L and again is now building this tool which helps structure unstructured financial data and sell it in a SAS Das model that's software as a service data as a service model Alex you ready to take us to the top hello guys great pleasure to talk to you again yeah we appreciate it we had you back on back in January of 2023 about a year ago at that point uh your Revenue was about 60% data as a service 20% software as a service uh and then 20% just pure Services what's the revenue mixed today what are you selling uh right now we are on around 50% of that of the data of service um 30% on on service itself and 20% on on S but everything has grown from there uh We've we had some interesting uh uh growth last year kind of 50% growth and this year we are we are probably reaching uh $1 million in revenues that's great so targeting a million in Revenue this year what did you end last year at uh it was kind of 800,000 yeah that was it that's great now who are you selling this data as a Service uh data too is it Banks and financial institutions yes uh actually originally um the the data we would sell to other intelligence platforms so we would sell to Bloomberg to Capital yq uh mood's analytics so these guys would get our data which is like financial data of private Brazilian companies and just put under products under on their sess uh and that's that was our original Revenue model um and well um after a while we started selling it to Banks as well so that's our Rush right now to to put our data directly into into Banks and not only in intelligence platforms um that that's part of our our priorities at the moment is capital IQ still paying you today are they still a customer sure yeah yeah yeah and what are they paying you for is it specifically I know you specialize in uh financial statements from private companies in Brazil are they paying you for all your Brazil company data that's right um they they are paying to have uh financial data of private Brazilian companies that we crawl in the web and and if your data is really valuable to somebody like Bloomberg or Capital IQ eventually don't they want to come buy you so that you don't sell your data to all their competitors as well they might but I don't think that that's uh a enough at the moment um I mean it's Brazil is a is a is a small uh Target for them it's not like well I'm the only one who has data of private American companies and that's a huge um uh competitive Advantage um it's braz is kind of a marginal Market to them so um I'm not sure if that that's something that would make sense at the moment maybe uh uh once we reach like five to 10 million Dollar in revenues that might uh make sense because our process is really unique uh it's been proven uh uh operationally and and in in Practical so uh um and financially has been growing uh but as soon as we escalate enough I think that that might be something they might look into because these guys they have uh their their thresholds for for m&a they're quite higher than our our size right now yeah that makes sense how many customers are paying you today oh directly might be 50 or 60 and indirectly might be 500 600 give me an example of an indirect customer um so I sell my data to CQ and to all these guys but I have some clients that they don't pay me for my data but they integrate in their product and they sell my module so these guys uh they have like 100 clients uh they use my module so that's the indirect indirect customer can you give an example of one of those companies where your module is built in sure um there's some guys in Brazil called nway um NE e o w a y uh they're quite big in the Big Data uh environment here and well they they resell our data in a in a module uh inside their product so if neoway in Brazil sells your module the Kook mod module for 100 bucks a month to end users how much of that $100 will you keep versus what neay will keep uh well when they distribute me they I I keep less than when I sell it directly obviously so I have I have large quantities but I don't have the uh um the value per customer that I would have selling directly but I don't have any any c as well I don't have any CA of acquisition uh of customers um so uh I would I would sell directly for roughly $300 to $400 monthly and they would sell me to like $100 monthly so same question though if neoway sells your module for a 100 bucks a month to an end customer what percent of that Revenue will neoway keep versus what will they pay you oh no that's what I would give they would sell it for a little bit more and then we we split it how do you contractually make sure that your value added resellers like neay don't uh cannibalize your own direct sales by decreasing your module price point inside of their Channel super low yeah it's an awesome question really good and the the the answer is well I don't I'm not sure about it uh I I don't have a way to make sure that they don't cannibalize it's more of a um um empirical conclusion like well um I think it's not cannibalizing I'm not getting any feedbacks that that indicate that that's happening and how we conclude it I see how many value added resellers like neoway uh drive you customers every month uh we have new way and another one uh called TTR okay so just two two big value added resellers that's right I see and T it's TTR domcom uh is TTR record.com I think it's transactional track records the the um um they originally sell data of uh transactions like uh abda uh EV abda multiples that that was their their primary business but they integrated out solution um and they are focused in Emerging Markets such as Brazil and uh other South American countries is it TTR dat.com uh let me check fairly I'm fairly certain it's ttrd dat.com but you can tell me if I'm wrong there um so those two channels do a lot of a lot of your reselling is that TTR yeah yeah so they do a lot of reselling you also go direct um H tell me more about your process I'm always fascinated because you know the whole world I mean maybe not the whole world but anyone potentially can get access right to uh uh private company financials in Brazil I imagine because they have to file something on some public domain but you have some unique process you use to get to the data to transform it to clean it to then spit it back out so that these Partners can sort of use it what did I just say that's not accurate or is all that pretty much true no that's pretty much true the the but the the thing that makes us unique is um the data is really hard to find so um it there are some sources that are easy to find but most of the sources are hard to find and we're the only ones that are investing heavily on on crawlers uh to to hard to hard to find sources and when I mean hard to find sources is not like oh it's a website that have everything structured and um and then it's just like a bot that goes there and gets the data and no it's it's it's a complete mess because the hard to find places is like uh thousands of different uh uh files that you don't know if that's a financial statement or if it's not so we have our Bots need to find out if it is a financial statement statement or not those files are in PDF format so um the data is unstructured so we need to to have other Bots that take the data out of the PDFs and then we have a quality assurance process with humans that make sure that everything is uh uh perfectly classified and structured um and we got pretty good on this routine of taking financial data out of PDFs and putting that into uh tables like Json or Excel or whatever so we started even selling this process to Banks uh Banks received thousands and thousands of uh financial statements in PDF formats every day and it's a complete mess to turn that into like actionable data and that's something we do very well actually I haven't seen anyone doing that as well as we do um uh anywhere else wh why why does this why do you guys have this DNA you know how I guess let me ask it differently how many folks are full-time today at Kooks 40 and how many are Engineers uh seven engineer okay and are you an engineer or no if I am an engineer no I'm I'm I'm I'm graduating in business and that Administration but well I C A little bit just uh it's been a necessity to you know try some stuff and make sure that we can develop some some things I Envision so I guess thousands let's say you get a data dump of thousands of documents it's they're in weird languages you're not sure if there even financial statements or not your your team of seven Engineers have built some some process to go analyze those I guess my question to you is isn't this something that one day sort of AI and and sort of these llm models take over in other words have you built some moat have your seven Engineers come up with something that open Ai and these other folks have not thought about where you will always be in need in terms of cleaning that data uh I I don't see um open Ai and these folks uh uh solving this this problem um so early because um when you go into PDF tables it there's a lot of things that ocrs don't solve so if if you don't have like a A system that goes into the PDF and structures that perfectly for the AIS to then take uh have an opinion over it um it it just doesn't work so the the technology needed to solve that is not the the the chat GPT or open AI technology is the OCR technology which um uh what's that stand for OCR OCR is a optical character recognition it's uh it's a system that that looks at a picture or a PDF and identify characters so it turns like an image to text so that's the that's the thing um there is a one uh specific problem which is a um like grammar errors um sometimes very often the the the systems they think that a g might be an eight for instance and and these confusions um um are not solved yet might be solved of contextual um nlps that might understand that in the middle of a a sentence of a word there's not a number then that's something that AI might help uh but uh um when you go into tables and and and when the the OCR there's another problem there is very very common uh they make confusion on line so they might put a value that is for assets in in current assets and this confusion is is tot totally deadly for our risk analysis yeah that's interesting do you have an example like on your desktop or something that you could screen share of some some some PDF you got that was that that open AI could never deal with because it's so confusing but your OCR technology is able to read it and extract sort of characters and and things that we can read in a programmatic way yeah the key thing is not exactly the OCR because the the OCR uh we we different uh uh ocrs bought in the market the the real difference is um is the process the quality assurance process we do over the OCR process so uh we have a system of alerts like hey guys this uh total assets is not equal to Total liabilities there might be something wrong here so our quality assurance team uh uh just goes into and and fixes the problem and we have like more than 500 alerts uh that make uh uh our our data get out of this process completely uh perfect and and validated that makes a lot of sense tell me a little bit more Alex as we wrap up I mean it's clear the technology here is powerful you've got big folks like Bloomberg and Captivate IQ paying for it how do you get more customers you know you launched this I remember back in 2022 we chatted you doing like 200,000 of Revenue 2023 you get up to 7 800,000 this year you want to break a million your bootstraps you're in full control which I love but is there any way you can grow this faster uh with Creative Marketing advertising but also stay bootstrapped uh yeah we have we have three different um uh products right so in our data as a service I don't see I I don't see that making uh the the big difference that would change us from a million to 100 million uh where I see that happening is is on our service that turns PDFs into um into structured data if we do that internationally if we can find the channels to to um to to go intern ational uh with this service um I think it's very unique and and uh the the like the big Tech folks they're not focusing on that right now so that might be an an advantage at the moment for at least a few years and I see our SAS as um as a nice catapult of growth and that's something we've never invested that much but we've been having really nice results in lead generation for the last uh four to to five months and uh that's making that's making us very happy and and um excited about uh what might come in the future for RSS solution well I'm rooting for you we'll see what happens in the meantime though let's wrap up here with the famous five Alex number one your favorite Business book oh favorite Business book uh sapiens it's not a business book right but it's book I like it works that works number two is there a CEO you're following or studying um I'm I'm super clich on the sort of questions I would say like Al musk at the moment number three what's your favorite online tool for building kxs um I'm still with the the answer I gave you last year I I love Google Sheets to to prototype stuff number four how many hours of sleep do you get every night oh 6 to8 okay that's fair and did you have a birthday are you 38 now I'm 38 that's right okay still single with one kiddo that's correct awesome last question something you wish you knew when you were 20 something oh sorry say it again something you wish you knew back when you were 20 years old oh um I would like to be less afraid of making mistakes I think that would have helped guys klook.com dobr was launched back in 2021 2022 he broke 500,000 bucks of Revenue in 2023 cleaning a Brazilian Financial data and selling it to Big firms like Captivate IQ and Bloomberg which many of you guys might actually you know listening might actually pay for directly some of that data is provided by these groups like KX he has specific OCR technology with a seven Engineers but then it's the human layer on top of that where they clean the data sort it filter it make sure and check for accuracy before they sell it off to the End Market uh that really is their secret sauce 50% of his Revenue today and they'll do about a million dollars this year 50% of that is data as a service another 30% is pure services and then 20% is true software as a service completely bootstrap selling through two major resellers in Brazil That's neoway and TTR data uh where he takes a cut of the sales there if he goes direct he's selling for 300 to 400 bucks per month and has over 50 customers to date Alex thanks for taking us to the top thanks Nate and great pleasure to be with you again

Introduction klooks.com.br now doing over fifty thousand dollars a month in Revenue up from twenty five thousand dollars a month just a year ago they have three business models that is selling all kinds of financial data to Banks they have a data as a service which is sixty percent of the revenue SAS which is 20 of the revenue and service which is another twenty percent of their revenue they've got a team uh today of about 35 folks 26 of which are in engineering and data cleaning uh they help these private Equity firms clean up you know balance sheets profit loss cash flow statements then also aggregate publicly traded data off the internet via scrapers and sell back to the big PE funds or the banks of the world hey folks my guest today is Alex Abu genre he is he's worked an m a advisory for the start of his career and was the CEO of a Manufacturing Company prior to being the CEO of K looks at K looks he's developed routines of structuring unstructured financial data integrating with ocr's automatic data classification quality assurance and also acted as a sales closer in their main contracts with large Brazilian Banks and international financial data aggregators Alex are you ready to take us to the top yeah sure all right this is a really tough space we rely on plaid data for example or teller or codat and so many of them mislabel transaction data in Banks and there doesn't seem to be a good source of Truth for this sort of thing is this the problem you're trying to solve uh yes it is in this uh in this environment but we we are specialized on um structuring data out of PDF files um which is a pretty uh uh difficult task it's quite a mess to to get financial data out of PDF files and put it into let's say tables or you know SQL or any other sort of uh um uh data format uh and we do that usually for for banks and um and we what we structure uh is is a financial statements we get financial statements from companies and we turn those uh those numbers which are pretty messy and confusing uh into something that um credit analysts investment analysts can use to to make decisions so for example if I run a large structured credit fund doing 10 million dollar debt deals into software companies and they're all giving me different formatted QuickBook exports of their of their QuickBooks files and they all have different labels I might just send them all to you and you will translate the labels the founder used with the internal labels that we use to triangulate the profit loss or the balance sheet with the cash flow statement something like that perfect that's that's exactly what we do um it could be a QuickBooks file could be a PDF file out of any accounting system uh we we get that into a structured format and then we classify it into the bank standards uh we do that for for banks and insurance companies but we also do that with public financial statements we have crawlers in the web getting uh financial statements there are public and structuring that into our database and that what that's why we sell to to international data aggregators interesting okay so are you would you say you're a SAS company or you're saying more of a service company uh it's a it's a bit of uh of both we have a assessed service which is a platform you can you know uh log in online with a password and and you can um navigate into our public financial statements Universe uh uh and that's that's our SAS uh but for banks we what we do is service we we so over the last 12 months what was the split would you say percentage-wise between service and SAS um it's there there's a third a third category which is like uh uh data to distribute to Distributors so we just sell like large amounts of data so people could distribute I would say that 60 uh would be uh uh data in in large quantities to Distributors and and Banks like public infrastructure uh 20 would be SAS and the other 20 would be serviced interesting so you really have what we call Das right data as a service is 60 of your business that's your main business that's our main business interesting interesting oh what's going on there YouTube good to see you guys now imagine this you love watching these interviews with SAS Founders but imagine if we took all of the valuation data out from over 2807 interviews I've done manually saves you a lot of time well we've done this we've built the into the beautiful interface inside of founder path check this out I'll show you how you can access this in a second but you log in you connect your stripe account you see your valuation real time you can see what it changed over the past 88 days and even set goals for evaluation this year now the secret valuation is there's many different ways to value a SAS business so the reason you're going to see three or four different evaluations inside of your founder path dashboard this is all free by the way is because depending on who's doing the buying of your SAS company you're going to get a different valuation a 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it's there's more tickets uh it's um 1800 gray eyes which is roughly let's say 300 400 monthly um and but when you when you go to to the the data structuring uh as a service to Banks uh we charge it by by unit we charge it by financial statement that we structure to them and depending on the on the quantity they heard from us it goes to from to an expensive unit uh uh a price to uh uh quite a cheap one and it goes from let's say 25 to five dollars uh at the range per financial statement interesting so if I was going to be a profit loss casual segment and a balance sheet that's five dollars five dollars five dollars so fifteen dollars total yeah that's it interesting okay tell me more about your team how many folks are full-time Financial uh balance sheet and income statements uh it's five dollars or we don't charge per um okay okay that's great how many folks are full-time at your company today calebs ah 35 more or less wow okay how many of them are engineers we have six engineers and uh uh more or less 20 people in our um data quality assurance and well the rest is like administrative sales and stuff how many sales reps do you have that carry a quota uh that's three people counting me oh wow okay you're the you're the head of the chief sales guy right yeah that's right all right very cool okay let's put this on a timeline when did you launch the business what year uh there are different views on that we started the business in 2012 but it was a side business to all the founders at that point um I turned into full-time uh CEO of the company in 2017. so well uh uh till 2017 the company wasn't really uh flowing uh it's starting to happen in 2017. and how many Founders are at the company how many co-founders we were three co-founders and we have one partner which is a fasting uh our CEO interesting now did you guys just split Equity evenly at the start or was it different we did equally ah so you guys are friendly you just said right 25 each 25 each yeah well 33.3 and well I had 20 33.4 uh the four so one had to have a little bit more but uh that's it we we opted to to do it equally that's great now have you guys Bootstrapped bootstrap today or have you raised capital no we bootstrapped it all the way along oh I love that all right and tell me about how you got your first customer oh actually we were accelerated and we had we at that point uh we received like 50 000 or something like that uh but we don't count that because how much Equity at the accelerator uh they never converted it uh it was an accelerator inside a big insurance company in Brazil and they just phased out the project and didn't convert any startups yeah they just lost money at that point okay so so um okay so bootstrap today that's great tell me how you got your first customer um our first customer was um wasn't an uh a private Equity that we knew uh were close to to them we uh uh from our city and they they had the the pain that was the pain that I had that I addressed uh specifically to this kind of guys at that point because uh I worked in lemonade I knew that private Equity firms needed that that sort of data uh financial statements from private companies that were public in the lab and the first the first one was uh was this private Equity company but um we the first real real customer that was that that maintained the business for for a while was um was a large data aggregator um it's um it was capital yq in 2014. so um they they basically didn't have any any data on private president companies Capital IQ was your one of your early customers yeah okay nice that's right that's great okay and then fast forward to today how many customers today oh let's um counting Counting the SAS might be because I had this we have the SAS we have the data as a service we have the the banks the banks might be like 10 more or less uh the our SAS might be something like 35 40. uh Big Data aggregators there are four or five and there are some guys that integrated our data into their systems and they sell that as a module and if you count those guys it's like 200 300 interesting so what does that mean I mean you're if I take that times the r pool the the Monthly recurring revenue average contract values you were talking about earlier I mean you're doing like 50 60 000 a month something like that um yes pretty much that's pretty much that it's um and if it's a good if you're doing that today what were you doing exactly one year ago so we can calculate growth oh half of it oh wow so you've grown 100 year over here yeah that's great okay so from call it 25 000 a month a year ago to fifty thousand dollars plus today what do you hope you can reach in 2023 um good question I think we can go to uh uh something like a hundred thousand dollars a month well we're certainly rooting for you I love that you bootstrapped here do you think you're gonna phase out you know two of the models and only focus on one I mean data as a service it sounds like it's the majority of your Revenue why not kill the other stuff uh that's a nice dilemma we have uh uh when talking among Founders um we we understand that data will be pretty much structured uh in the future so we don't want to quit sales right now it's a small part of our business but we understand that in the future like 2030 plus uh it might be uh the main business that we have because uh um structural data we will will become easier with time but creating intelligence out of it uh will not be commoditized so so early that's that's what so that's why you don't face out the others because we're looking for 2030 and on makes a lot of sense all right Alex let's wrap up here with the famous five number one favorite book our favorite book um sapience number two is there a CEO you're following or studying um well I'll be very cliche it's on Steve Jobs but you know number three what's your favorite online tool for building K looks my favorite online to ah I'm not the deaf I I'm the guy that uh that tries stuff and I I love to do things in Google Sheets and like prove to the devs that things work and then guys look I did it on Google Sheets so please put that in production it works more or less like I love that number four how many hours of sleep do you get every night oh depends on the time of the year but might be seven I'm a good sleeper fair and what's your situation married single kids I have a kid but I'm not married okay not married with one kiddo and how old are you I'm 37 now 37 last question what's something you wish you knew when you were 20. uh I I think that when I was 20 it would be good if I was less afraid of making mistakes dried stuff harder guys there you have it klooks.com.br now doing over 50 000 a month in Revenue up from twenty five thousand dollars a month just a year ago they have three business models that is selling all kinds of financial data to Banks they have a data as a service which is 60 of the revenue SAS which is 20 of the revenue and service which is another 20 of their revenue they've got a team uh today of about 35 folks 26 of which are in engineering and data cleaning uh they help these private Equity firms clean up you know balance sheets profit loss cash flow statements then also aggregate publicly traded data off the internet via scrapers and sell back to the big PE funds or the banks of the world anyways we'll see what happens next Alex thanks for taking us to the top thank you it was great talking to you one more thing before you go we have a brand new show every Thursday at 1pm Central it's called Shark Tank for SAS we call it deal or bust one founder comes on three hungry buyers they try and do a deal live and the founder shares back-end dashboards their expenses their revenue our poo CAC LTV you name it they share it and the buyers try and make a deal live it is fun to watch every Thursday 1 p.m Central additionally remember these recorded founder interviews go live we release them here on YouTube every day at 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