How Knowd CEO Justin Shum grew to $330K revenue with a 3 person team in 2025.

guys node.ai got going call it six months ago research and they just closed a 500 000 convertible note with a 10 million cap so call it that sold five percent of the business pretty healthy though the question now is can they get uh MBA students as their initial ICP Target can get these students using the Tool uh and then after that can they start turning on a revenue stream here we will see what happens Justin's got experience though what two time exited first time exited founder second time exited founder bootstrapped BC note is this third project we'll see where it goes hey folks my guest today is Justin shum he's building node.ai which extends human reasoning and decision making abilities he's building on his own experience it's a three-time Founder one bootstrap one exit and one Venture back to Justin you ready to take us to the top absolutely let's do it all right what was the name of the bootstrapped one yeah ready chat founded back in 2013 exited in 2015. ready chat okay and what was the uh you bootstrapped that right yep you got it so like No No Angels you just put in your own money basically yes that and a lot of Blood Sweat and Tears yeah and how many years was that again you said uh we operated for three years and then we had an acquisition okay and did you I mean did you guys break a million bucks of ARR at that point or what were you when you exited we were pretty close in terms of Canadian dollars uh if you converted that to USD yeah it was uh it broke a million and because it was a hybrid between you know software and services we didn't get a huge multiplier on it it was about 3x Revenue uh for the opposition okay uh this would have been back bootstrapped entrepreneur that was a lot of money for us at the time yeah I mean what that's a three million dollar deal back in 2017 right you guys own how many co-founders uh there was three I mean so if you each can pre-tax take home something like 300K that's a good gig back then yeah you know what and in Canada you get uh your tax free up to 750 000. so it was basically all of it in our pockets which was nice that's okay so I changed my math you each get 350 000 uh pre-tax and get to chemo so that's something like that yeah that's great looking back do you go man I wish I kept building that thing there was a lot of potential there did you sell too early or no yeah I think every founder has uh seller's remorse for sure um but you know that was a it was somewhat of a platform that launched us into other businesses and you know all of us are um you know successful in in different areas now so um I don't think I have too much ruts yeah I I rarely meet Founders that regret their first sale because it creates so much optionality for you not to mention the cash in your pocket um so all right you get that done in 2017 and then what was the next company I guess this was the BC backed one this was actually not we um the second company was ask Avenue again in the prop Tech space What uh ask Avenue okay and uh you know we had some of the largest Enterprise customers at the time Remax um you know a royal page another massive brokerage with 20 000 agents um and we got a lot of press want to pitch competition to kick it off uh but that one was angel-backed actually and it was a completely different experience from you know bootstrapping where you own I own 51 of ready chat uh ask Avenues slightly less but it's super important to note this that taking on Angels they have to be the right Angels uh the angels we took on were not um experiencing investing in Tech and so they had different agendas different strategies they were trying to enforce and so it got pretty messy pretty ugly and I actually exited that one willingly um and didn't make too much money off of it I just wanted to to move on to new things why do you say ugly yeah just different objectives um you know they were opposed to the markets we were entering the go-to market strategy um and there was just a lot of uh debates um you know a lot of bats which led to backstabbing eventually so it became somewhat of a toxic environment backstabbing yeah yeah yeah so for example you know I was the CEO at the time and I really wanted to continue to go after Enterprise uh within real estate um continue to go up market and just double down on that segment uh but they wanted to expand uh into other verticals um and So eventually you know it came down to you know voting and and I was outvoted and and I was actually removed from the company uh but I was willing to leave interesting what was the board how many folks there was I believe six people at the time wow that's a lot of people on a board for a company at Angel stage yeah yeah so you can imagine how complicated that was well yeah and you and also you rarely I mean you don't want to have an even number on your board because then you have to deal with ties um exactly all right what was the third company yep third company is um node which I'm currently working on uh this one's venture-backed so I've gone through you know very structures and I can say that this one is a lot easier when you're Venture packed you have just access to Stronger advisors more resources and you really can I wouldn't say take your time but you can really methodically plan out you know your next steps you're not trying to put out a bunch of fires trying to you know make payroll or anything like that you have um more time and focus I would say 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 VC is going to pay a different valuation private Equity Firm is different if you're going to do a minority sale that's different and if you sell the whole business that's a different valuation you can see all those when I hover over here here right so the teal is what a VC would pay yellow is what private equity and red is if you sold the whole thing outright now what's cool about this is this is not built off random data again you guys hear these interviews on YouTube all these datas are built from real-time valuation data points Founders share with us on the show so traction 1.2 million seed round 3.7 raise they sold 22 percent of their business go in here and filter by the event maybe you only want to see companies that have sold the whole business well here are a bunch that have been acquired the valuation and the multiple maybe you're going out right now and you're raising your seed round well go in here and look at all this recent seed deals that went down what they raised what valuation they raised at and what percent that they sold there's never been a larger data set of SAS valuation than what you can get now inside of founder path and we're thrilled to bring it to you all right we're gonna go back to the YouTube video here in a second but if you want to check this tool out if you want to jump in and sign up you can check it out for free to get your valuation at this link this link founderpath.com forward slash products forward slash evaluations or if you go to founderpath.com and hover over products click on get your evaluation here and go ahead and sign up to give it a whirl again all that valuation data live right inside the platform I hope to see you there all right let's jump back into the interview so what do how much did you raise in what year yeah so we just closed it actually um last month um so it's precede uh 500 000 USD from Drive Capital amazing Partners um we're contemplating taking on a little bit more for our our precede with um I don't want to name them yet because it's not not done but um their resources in Ai and we're building an AI space uh would be invaluable to us so we're considering open up a little bit more and then maybe we'll raise a either a small a or a larger seed in about six to eight months time what cap did you negotiate um so it's convertible note um sorry what was your question what cap did you negotiate or was it a or was it an uncapped convertible note it's capped yes um I I don't want to get into too many details but I will share that we did raise like we're probably in the top 10 in terms of valuations and terms um we came out of a a program called entrepreneur first not sure if you're familiar with them that's where I actually met my co-founders this time around um and their terms were like ten percent for like 200 000 uh not the not the greatest and so we actually um we actually um didn't go through with that with that term sheet um we actually decided to hit the market um the open market and we secured um the 500 at five percent um instead of the ten percent so much more favorable did that I mean so that would be a 10 million cap yeah valuation yes um well there is no evaluation on a say I mean there's a cap of 10 million right so when you use the word valuation what do you mean so it's five percent out of 10 million value uh valuation and then the conversion point is where the cap comes into play um so it is uncapped rather I see yeah got it point being you sold five percent of the business once it converts at for 500K you got it got it um that's a high valuation um that can be a bad thing because you have to grow into it it also resets the pricing of your options makes it harder to recruit uh or defend a lower 409a valuation why'd you optimize for valuation yeah you know what we that wasn't our plan um it was more so how we looked at it was we can get more money for the equity um but we're also building an AI space and we're going after a pretty large market so we feel that um the valuation wasn't too steep for us all right let's talk actually about the product so who do you plan to sell this to and how they use it yeah our initial ICP will be um actually MBA students why MBA students well they're they're not tight on privacy and you know we need your data I hate this idea aren't all MBA students broke they are but here's here's the thing so why would you pick them as your initial segment if they're broke I wouldn't say they're broke I would say probably 50 of them are actually working uh in the field doing part-time MBA the ones that are like right out of undergrad and train their MBA yeah they're broke but here's the thing they're open to trying new technologies and we're really looking for the feedback as opposed to monetizing them we want them to help us Define our roadmap um if we why would you build a roadmap around a customer that's broke don't you want to build a roadmap around a customer that's rich well here's the thing they grow up into Enterprise organizations and they're gonna if they adopt us according to our plan they'll take us into their organizations as well so that's the strategy on top of that they mimic our core customer that we plan to monetize with which are management Consultants they do the same thing in terms of analysis um and and they deal with a lot of unstructured data and documents and things like that I see when did you what month did you write the first line of code for the platform we actually just started writing last week so we've been building my our co-founders my co-founders and I we've been building across three different continents for the past six months and before we wrote any line of code we went through deep discover we went we went through a dozen different rabbit holes to arrive to this final conclusion where we ballot you know invalidated our hypothesis before we started writing and building unlike my previous startups where we just built and started selling like I sold packages in my previous startups before we even had a product or service um so this one was a lot more methodical in our approach I mean how do you know I mean no one's ever come to me and say um I test my hypothesis and it failed I'm not going to start a startup anymore right everyone figures out a way to make that a good story so I mean what were you looking for and what were you testing specifically yeah we were trying to unlock value like while building an AI um it's it's it's scary because literally every release of um from open AI kills hundreds of startups right every single feature um and so we didn't want to build something for the short term um and so we really had to understand what value we could offer long term while while thwarting off threats from companies like open Ai and how do you know what open AI is going to release six months from now what if they release this product you have no way to know that well you can kind of understand where llms are going to go um firstly you know it's it's it's you know text-based like simple stuff and then now they're getting to multimodal so you know video audio um and you can kind of like Trace where what what type of different things you're going to be able to do with the llms for those different types of formats um but for us we looked at the big picture and we realized yeah you're right we don't know what they're going to release it's going to disrupt a lot of startups but everything is going to be chat based and conversational based and so what we're actually building is a platform that's really easy for anybody to get into to start using and finding value with llms without having to prompt um so we're designed it comes down to design principles and we see a prompt this future you shouldn't have to converse with your machines in order for them to extract value from them and I'm taking these learnings from the chatbot era right I built in a chatbot era as you know chatbot went through a huge chat box went through a huge hype cycle and then they fell off because they just sucked yes chatbots are a lot more intelligent now but you probably have experienced the chat GPT you understand that prompting the slightest changes uh variations will result in a completely you know different outcome and output and we're trying to eliminate that variance by again creating a product that doesn't require prompts I mean anyone listening is going to go well how are how has your system going to know what I want automatically without me prompting it yeah absolutely so it really starts down comes down to the metadata that's available to us in the context of the actual data that you're dropping into our system so I mentioned earlier that we're we're dealing with unstructured data first this is in the form of PDFs uh video interviews similar like this you'd be able to take this recording drop it in we would transcribe it we would understand the context of those conversations and then we could have Auto suggested next steps uh very similar to like a chatbot experience now this I hate saying this and comparing us to this but when you have when you're chatting with the dumb chat bot it has like the decision trees the little buttons that you can select for a different outcome so we're actually providing we're still leveraging prompts but we're offering Auto suggested prompts for a user to Simply select next output um and and so they go through this decision tree and then we're capturing that in a visual way so that you can arrive to a conclusion or a desired output and then backtrack to see you know what variants you can or changes you can make for a variance on that output um unlike you know a conversation interface all your prompts get lost how do you know what variants though that the user wants to drive yeah so for example if you were to drop in a PDF let's say a Tesla earnings report maybe past two years and he wanted to run some analysis and compare those those two years into certain segment product segment you could drop them in and we could but that's a prompt I would have to Pro I mean I'm prompting What You just defined as a prompt well you're not though because you're dropping both in and we know automatically there's two different folders We can identify our files we can identify the relationships and then have Auto suggested products because we know you probably want to do some type of comparison um and and so that's the design those are the design choices we're making how do you know just from me dropping in two different PDFs that I'm wanting to automatically compare them what if I'm going to concatenate them and put them together yeah absolutely um so there are options various options which open up different drawers um to simplify that process but isn't that a prompt it's an auto suggested prompt that you're selecting you're not there's no cognitive load for you to think how should I phrase this for a desired output so we're eliminating that isn't this the whole Like Son asks mom go to supermarket the son asks mom for strawberry jam the supermarket mom shows up there's 20 different strawberry jams she ends up buying no Jam because she doesn't there's too many options I mean isn't that what you're doing here sure yeah but what's great about us and this is what's somewhat proprietary is the user interaction data that we're going to get from these MBA students who are going to tell us what is the most accurate response or outcome or power but the mom didn't buy any jelly the supermarket learns nothing she walked out hands empty there were too many choices maybe maybe in that example but we think we think it could be different and and more efficient in the way why how do you incentive as an MBA to spend their time to teach your program how to work and then you're going to turn around later and charge them for it you know what it's about it's about understanding your ICP we're not trying trying to do this for every vertical and so we understand that MBA students as well as consultants leverage a dozen different Frameworks that's the outcome they want they want to be able to do an analysis and apply framework and so if we understand that desired outcome then we can help that's a prompt it is a prompt but they're not having to prompt it you're right because the set number of pro like you know when MBA it wants to compare the Tesla earnings report a to B it that the reason that they don't have to prompt is because it's a defined because of who the ICP is it's a defined problems you got it yeah we are still leveraging prompts but the the as the user you don't need to prompt yourself you don't have to deal with that and it reduces the cognitive load how are we going to make money on this yeah great question so we are actually taking we we see this as you know we're trying to actually disrupt platforms like um Wikipedia we think you know the single simple web page um encyclopedia um hasn't evolved and so what if we could give creators um anybody who wants to discuss and analyze and create a community around a topic the ability to create intelligent workspaces where they can run analysis analyzes and then users uh their followers could Fork their analysis create their own add to it add more data sources to it and then build communities around these types of um you know topics so again going back to the Tesla earnings report huge huge Community around you know retail investors around Tesla earnings what if you had created a node board and had this this analysis and had a community contributing to it as well so this is living breathing evolving type of workspace and that's our vision and go to market strategy all right we'll see if it works in the meantime let's wrap up with the famous five number one your favorite book okay favorite book oh man I think it comes down to what I'm reading actually favorite book is a sales book how to pitch anything from orenclaffling entrepreneur looking to get started in in business they need to learn how to sell that book is great in terms of framing conversations number two is their CEO you're following or studying there are so many so many um I think Sam Altman is like amazing to follow um very unassuming extremely intelligent um really interesting to follow him right now number three what's your favorite online tool for building node favorite online tool I would say because I'm not non-technical I would say Miro has been extremely helpful for us number four how many hours of sleep do you get every night oh that's a loaded question you know I used to be about four or five hours of sleep now I've prioritized it as my number one thing objective of the day even before work um so now I'm getting about seven hours that's great in situation married single kids um I am single I do have a son who's eight years old oh very cool okay and how old are you I'm 38. 38 last question something you wish you knew when you were 20. I wouldn't change a thing so ignorance is bliss I would like to know the same um as I knew back that and follow same path guys no dot AI got going caught six months ago researching ages closed a 500 000 convertible note with a 10 million cap so call it that sold five percent of the business pretty healthy though the question now is can they get uh MBA students as their initial ICP Target can they get these students using the tool and then after that can they start turning on a revenue stream here we will see what happens Justin's got experience though one two time exited first time exited founder second time exited founder bootstrapped BC known as his third project we'll see where it goes Justin thanks for taking us to the top thank you so much Nathan have a wonderful day everyone 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 2PM Central to make sure you don't miss any of that make sure you click the Subscribe button below here on YouTube their big red button and then click the little bell notification to make sure you get notifications when we do go live I wouldn't want you to miss breaking news in the SAS World whether it's an acquisition a big fundraise a big sale a big profitability statement or something else I don't want you to miss it additionally if you want to take this conversation deeper and further we have by far the largest private slack Community for B2B SAS Founders you want to get in there we've probably talked about your tool if you're running a company or your firm if you're investing you can go in there and quickly search and see what people are saying sign up for that at nathanlacka.com forward slash slack in the meantime I'm hanging out with you here on YouTube I'll be in the comments for the next 30 minutes feel free to let me know what you thought about this episode and if you enjoyed it click the thumbs up we get a lot of haters that are mad at how aggressive I am on these shows but I do it so that we can all learn we have to counter those people we got to push them away click the thumbs up below to count on them and know that I appreciate your guys's support all right I'll be in the comments see ya