Onepanel Revenue, Valuation & Funding (2019)

hello everybody my guest today is don scott he founded taizu robotics and dslr pros forging partnerships with dgi hitting uh 10 million in annual sales and his background in technology development and orbital orbital atk missile systems and u.s navy and cyber security at experian sony and warner bros now general aviation pilot having owned and operated several types of aircraft he's also a triathlon enthusiast training for an ironman but in the meantime focused on his company one panel workflow automation for computer vision don you ready to take us to the top absolutely all right man so what do you like people calling you by the way donner donald dawn's fine don very good all right so i'm a little i'm a little confused here what did you do with dji and how does that relate to one panel uh so we actually built a robotics platform we leveraged a lot of the dji drones this is much early on and one of the one of the biggest challenges that we were faced with was how do you efficiently find uh data scientists computer vision experts and how do you actually scale a compute environment to actually build an object tracking model or platform and this was back in 2013 and 14 it was very difficult to do and ever since then uh we one of my uh friends actually his name is russ tehrani he actually started to look into how to leverage kubernetes very early on and how to scale a compute infrastructure environment and uh we started the company and now we're able to scale almost nearly infinitely across um kubernete using kubernetes native for any type of uh computer vision ai workflow right now very cool now when was founding date what year uh we we founded one around november december 2017. okay 2017. and then um obviously scaling today what's the revenue model is it a sas company or how do you price uh so we actually have two different models we have a cloud based offering more like a platform as a service where you can uh you know we have a monthly subscription fee but also uh we charge for compute right so if you're using if you want to use a gpu 8 gpu cluster v100 you know we'll charge you per second for that our other pricing model is we offer a on-site on-premise deployment option so uh you could then you know we would you know you would we would charge you uh per seat per node perhaps uh depending on the organization depending on the size scale that you need so in other words one panel can not only provide you with a cloud-based platform as a service but you can deploy in a hybrid configuration on-premise or um you know in any you know private cloud if you wanted to as well if you're like a government for example um you're doing facial recognition uh you don't want to put all your data in anybody's cloud you can we can deploy our platform like an operating system do you sell to china uh we actually are working with some folks uh potentially in china mainly aws and senate cloud we see that there's a huge opportunity for uh providing a way to scale infrastructure for uh product-based companies um you know we're looking to help them uh provide uh you know access uh this type of scalable compute they don't have that right now so uh we do have some client customer chinese customers right now we're looking to expand them to china very very considering the current macroeconomic environment how on earth are you convincing to be okay with an american company potentially owning part of their data so the partnership for us wouldn't be um you know our our instances keep in mind that we are deployable on any cloud so imagine tencent or alibaba cloud uh you know using our software as an on-premise type of platform right so they would offer that separately um none of our data would be held you know our us or european data would be held in in china whatsoever it would be an offshoot if you will of uh of of one panel and mainly it's going to be around the marketing and sales engine for a one panel type of instance in china sitting on top of alibaba cloud or aws out there interesting okay i know you have a lot of different customer cohorts but give me an average you're on average what's the customer going to pay you per year for full deployment of the platform so it depending on the type of customer so right now we see users spending close to you know several thousand dollars per month on our platform that's just on the compute uh but also uh you know we're partnering up with by cloud factory uh some of these annotation companies and they can they can uh you know consume about maybe four or five thousand dollars worth of uh annotation related work and since our platform tightly integrates with that annotation workflow for computer vision um we can actually do pre-annotation using gpus so we're expecting that uh that consumption of uh gpu infrastructure for annotation scale up quite right what is an annotation so annotation annotation is a you know taking an image or maybe it's a video feed say you're dropping two gigabytes worth of video from a self-driving car um and you want to identify hey that's the person that's a bike um that's a pothole don't drive over that so you'll have somebody in india the philippines or even africa drawing a box around it and labeling that's a pothole that's a truck that's a car example oh my gosh yeah you do it automatically we can actually help pre-annotate that so we once the initial data sets are are annotated classified we can then build a model or help them build a model or use a third party uh to help build a model that uh basically populates that uh that that bounding box if you will ahead of time so now it becomes a qc function uh we literally popped we literally annotated 22 000 objects in less than 45 minutes imagine how long that would take you and and days and not thousands how much are you doing how many how many annotations are you processing monthly right now across your entire base so i'll give you an idea one of our customers processes close to 250 terabytes per month on our platform right now what does that mean in terms of annotation uh annotation is uh thousands of dollars per customer uh we have it's it's hard to quantify right now but i can give you on average what our customers are doing in terms of uh volume of data right that's how we measure it yeah what i'm the reason i'm asking these very specific questions because i'm trying to get i want to make sure that i give some um example that my audience will understand that relates back to how much data annotations and how you just described it i think everyone understands what those are so i was wondering if you had a number i assume it's in the millions across your entire base uh so in terms of so we look at in terms of gigabytes and terabytes right so let's say you take a gopro camera you drop in uh maybe a gigabyte worth of data so out of that gigabyte we can pre-annotate 22 000 frames or objects and the number of hours associated with that would take you know a couple thousand hours per month if you multiply that times uh the number of workers doing it you're looking at maybe four to five thousand dollars per month for that one individual so we have close to two almost close to two thousand uh users on our platform now um we have maybe five to ten percent are actually using annotation at that particular volume right now interesting um when you say two dozen users are they all paying customers or is there a free plan we do have uh some free access to the platform that's our total uh user base around 2000 uh we are starting to onboard more larger enterprises right now where um you know you'll we'll be looking at uh you know you know per seat per node type licensing around that yeah so you launch 2017 and then fast forward to today about how many customers have you actually have paying are we talking like 20 it's an enterprise player is it 200 or more well over 200 okay sure yeah well i mean by the way i'd prefer you just give me the accurate number so it's less than 2 000 but more than but more than 200 is it what's the actual number paying customers i i don't have the data in front of me right now but it's it's uh because some each customer will pay at different levels right so some might be teams um you have individuals that are paying uh maybe intermittent uh intermittently right so they'll come on for a couple a couple weeks or a couple months to actually run compute to build some models then you'll have annotation so it's actually sporadic that it depends over the course of the year okay but i guess maybe the right question is over the course of the year right how many customers will pay you something to do some you know use your technology some way uh well over you know 200 to maybe 500 uh okay okay fair enough so a good portion of your of your free users are paying call it 25 30 percent yeah roughly yeah interesting okay and and kind of how did you get your talking back to the the founding days 2017 what was the struggle like on your first kind of 10 customers how'd you find them yeah that's a that's a good question um i think mostly it was word of mouth through our accelerator we went through a accelerator out of minneapolis called generator and we you know uh they actually exposed us to a lot of interesting companies from like cargill to a lot of startups and how we got our first customers was really to say look um we part we started to partner up with uh different uh ai consulting firms um who are who specialize in different types of ai model building and uh what we did was we connected them together on our platform that seemed to be the magic formula interesting yeah being able to talk to a company who doesn't have any type of ai maybe they have one data scientist maybe they have none but what we're saying is like look hey we can help you by you know helping you almost quote unquote outsource ai to different parts of the world collaborate on our platform keep the data all in the cloud make it simple make it secure and uh you know keep the you know the cost down to actually do that and it's been a success so far and so have you guys decided to to raise capital and and take you know obviously take dilution if you do that or have you stayed bootstrapped uh so we we were initially bootstrapped we have raised uh 1.2 1.3 we're going to make an announcement officially but we've already raised our first seed round and if we can hit our mrr expectations by uh hopefully in the next year and a half we'll do a raise a series a yeah where do you hope to be in terms of mr in the next year and a half uh hopefully 400k mrr okay that's our target and what would that be from in terms of where you are now doubling tripling i i don't have the exact numbers we've been really uh working on scaling our platform right now so uh i'd have to i'd have to dig up those numbers exactly well what number i mean you just told me you want to get to 400 000 a month obviously you know you you do that based off a growth rate of what you're currently doing i assume you know what you're currently doing you're running the company uh well actually i'm i'm the uh co-founder i do most of the biz dev type stuff okay well same as our ceo yeah yeah he could we could provide that to you later but i i think um you know i'm just generally i'm just generally understand a seed stage company that's raised 1.3 million dollars what are you trying to hit in terms of growth rate most would say 3x year over year when you're this small some would say 2x once you get 30 40 million bucks an arr i'm generally trying to understand what you're trying to target growth rate-wise uh so we're at well in terms of users right now we're at about 37 growth year over year on our just on our user base uh revenue we're actually pivoting to more of an enterprise model so i don't know exactly what that rev that growth rate will be so it depends on a couple of big contracts that we have coming up and depending on that it'll help us determine whether or not we're going to hit that uh 400k where did you finish out at last year or were you had you not turned revenue on at that point uh we were very low again i don't know the exact number uh so i would have to yeah a range is fine yeah i don't know i don't know what it is to be honest i'd have to i'd have to look it up for you you know donna range is fine yeah i i i'm not sure i don't know what the range and i'm not sure if we want to give out that number right now to be honest okay well you told me you're trying to hit four hundred thousand dollars that's what you're trying to grow to um i find it really hard to believe that as a founder you don't know what your revenue was last year that would be like serious red flags from any investor so i think what actually is happening is you don't want to share it for confidentiality reasons but you've already shared what you're trying to grow to right so i'm i guess you put performance together in terms of how you're modeling your enterprise plan where you're pricing per seat and per node right so all i'm trying to understand is are you going from like a dollar to 400 grand or already are you already halfway there you want to double your every year you must have some idea of the general range of growth so yeah so i you know we're less than less than a hundred grand per year let's put it that way for our very first stage because we're initially targeting per year per month per year okay right so right now you're doing less than 100 per year in terms of run rate correct now now exactly what we're trying to do now is get to more of an enterprise type model and we have an interesting way to achieve that and that's our that's our target okay that's that's really helpful so just to repeat that back to you because i want to make sure i get it accurate and thanks for thanks for doing that currently today you're doing less than in terms of run rate less than a hundred thousand dollars per year however you have a healthy user base of 2 000 of which 300 are paying something and you hope to now launch this new enterprise plan to grow to 400 000 per month or about 4.8 million dollars in terms of run rate up from 100 grand today that's correct okay very right yeah very cool all right what is the so so first off what turned you on to the enterprise idea right you were doing one thing and now you're going to kind of pivot to the enterprise play what gives you confidence in that model uh so we're actually seeing a lot of uh inquiry on uh being able to deploy our platform at within their own data centers right so uh for example there's a country who's interested in deploying facial recognition and they do not want to deploy their their software in any cloud right so they want to buy their own hardware they want to deploy it locally and that means significant more revenue per month for us so we see that as the way to go right now just because of the level of interest where we're getting right now for an on-premise type deployment or even a hybrid deployment for that yeah this is a big league totally away from the wife this is a big leap though i mean if you have 300 customers right now paying right and you're doing 100 grand in terms of annual revenue that means each customer is paying on average like 30 bucks a month you're now going to go to i mean these are going to be i mean you're going to increase by a factor of a thousand almost you're looking at close to potentially million dollars a year and uh in licensing fees perhaps for countries uh for cities uh i mean you're looking at a significant amount of revenue from why would someone invest a country like china right or tennessee these massive cities councils whatever invest and have confidence in paying you a million dollars a year when you're a year and a half old company with less than 100 grand in revenue right and one point very little money raised yeah because there's aren't too many options on the market right now for a fully scalable kubernetes native workflow automation platform there are just aren't any choices out there well is there a reason there are choices maybe there's not a market for it uh there definitely is and you're seeing a lot more popular kubernetes is actually pretty pretty new last maybe five years became becoming popular within the last three so what we're seeing is that companies are these these these companies countries they don't have a way to easily scale where they have to go to google uh they have to go to aws to do that right that means you'd have to hire a team to actually go out and build out your kubernetes infrastructure you'd have to test it it would take you just a long time just to be able to do that not to mention finding a resource it's very difficult to do yeah so being able to have that same google aws type of scalability in your own private data center is huge yeah no by the way i'm a big believer in again kubernetes right fusion off came on my show about a year and a half ago brian did and basically a lot of their growth has been its identity and user management has been tied to docker and kubernetes containers right so like i'm a big believer in kubernetes i'm just saying i'm interested in how you're going to convince you and your founders are going to convince these you know million dollar deals on a company that's basically nothing right now that's a big trust factor to a government that's buying right it is and i think it's just uh you know some of the demos that we've done they've been extremely impressed and uh you know working with our partners and that's the other way we're gonna scale this as well too it's not us trying to sell it right we're actually partnering up with what we think are you know channel partners right these are consulting firms that actually do the work itself that are building the facial recognition models um they have the info they're building it they need infrastructure we onboard them right and they recommend us to their customers that's exactly how we're actually going to scale that's how we're scaling right now what's the team size today how many folks uh we have a total of 20 of five uh full-time employees we have consultants and contractors and do you know anything yet about churn and expansion revenue or is it too early uh it's still too early we're focused on building a really kick-ass product and we think we're almost there we're very close and uh we should see some some pretty big enterprises uh coming on board very fairly soon you obviously raised to help cover burn to buy you more runway to close these enterprise deals how aggressive are you being with burn we talking 100 grand a month or more uh again i i don't know there's exact numbers right my focus is on getting new business um being able to find these customers but i think we're doing pretty well on burn we i think right now we have a good 16 or 18 month runway right now based on our uh our burn rate okay and you just raised the 13 or the 1.3 million yeah not too long ago that's correct yeah yeah okay yeah so if you again if you raise 1.3 million to cover burn for 16 months that's about 80 grand a month [Music] uh yeah something like that i guess i'd have to look at it yeah were you involved in the fundraising conversations at all or your other co-founder handled that exclusively we both we both did it okay different we both handle different aspects of it yeah i'm just surprised you wouldn't know like i mean burn is like the number one thing you're thinking i mean that's why you raise capital you just gave up equity and you don't know what you gave up the equity essentially for is what you're telling me yeah no we're actually we're actually doing pretty good on burn matter of fact we just had our investor meetings and everybody feels confident where we're at right now yeah yeah i mean again pretty good as a relative term that the numbers allow anyone to kind of make a judgment on that but again if you covered you know 16 months of runway with a 1.3 raise that means you're burning call it 80 grand a month net or something around there per month that's that may be accurate yeah well why would it not be those are your numbers yeah they're accurate yeah okay all right let's wrap up here let's wrap up with the famous five number one what's your favorite business book uh you know i'm reading this book he uh i forgot the name of it actually i just uh just started it um uh it's about he's a he's an xcia spy but he talks about how to influence people um yeah i forgot the name of the the book i'm about three quarters of the way through how to put it down for a little while in the airport not a couple months back is this like survive like survive like a spy or one of these books that's it that's exactly right yeah awesome book it talks about how to actually get out there and really uh you know start the network it's more of a you know how to uh you know how to how to really build those relationships that's that's uh that's primarily what i do right number two is there a ceo you're following or studying [Music] not at the moment okay i think that's okay number three is there what's your favorite online tool for building your company wow uh man intercom uh is is pretty kickass right now um you know google we love the google guys we love aws those are pretty much our go-to platforms and tools right now but again if you ask if you have to rush our code our the ceo and co-founder he'll probably tell you more you know technical uh technical tools yep uh number uh number four how many hours you sleep to get every night four and what's your situation married single kids uh married any kiddos uh no kiddos just the dog uh sitting in the background right here my wife works for google so it's uh you know it's a challenge for all of us right now she's in hyderabad oh so yeah very fun how old are you i'm 44. all right last question what do you wish your 20 year old self knew wow um say that again what was the question that's okay what's something you wish your 20 year old self knew wow just be persistent just keep working at it don't let anybody tell you you can't do it don't get distracted keep focus and you'll get there guys there you have it again one panel workflow automation for computer vision they currently have 300 customers doing less than a hundred grand in terms of annual croring revenue hoping to scale up to about four million bucks in a run right with this new seed round of 1.3 million team of 20 people uh burning caught between 16 and 80 thousand dollars per month again as they look to scale really betting on the kubernetes platform don thanks for taking us to the top no problem awesome thank you