How Allstacks CEO Hersh Tapadia grew Allstacks to $3.3M revenue and 45 customers in 2024.

hey folks my guest today is hirsch tapadilla he's the co-founder and ceo of all stacks the first software delivery intelligence and predictive forecasting platform helping engineering teams predict and quantify team productivity he's led teams like this across sas pharma medical device and supply chain and previously was co-founder of several ventures including ravioli labs an ml driven consulting firm certi rx an anti-counterfeiting solution for supply chain and med count a medical device for infectious disease diagnostics he's living in raleigh and is a graduate from duke and nc state hershey ready to take us to the top yeah absolutely all right where so where did you experience this problem was it when you were at you know ravioli labs or certain rx where did you find this problem yeah it was it was everywhere actually so i was running product engineering teams i think the the healthcare background created the exacerbated version of the problem because you have two layers of translation so when you look around your organization and you see marketing sales customer success everybody's really instrumented really data driven and engineering's not and then you have to further explain it to somebody who has maybe a more of a healthcare science background you're going through two layers of translation without any data and it was just always a point of frustration for me which is like how do i how do i help quantify this in a way that actually helps me advocate for my teams why are my teams actually doing really well what does really good look like yeah for my for my audience listening this is the use case of there's that annoying trello card that has been sitting in the doing this week for the past six weeks and for the business person it looks like no momentum is happening but everyone on the dev side knows there's a bunch of work happening so you are able to basically get insight into that insight into that and then help you understand when is that actually not happening as well so both the positive and negative outcome we're doing all the work that that we should be doing but there's other externalities that are causing it to go off track as well maybe it's really a lot more complicated than it is normally and so being able to highlight all those outcomes so then you can make a decision right your business counterpart can say hey i understand that this is uh this is going differently than it normally does i'm going to make different decisions now and so one of the things we think about a lot is how do we give agency back to all your stakeholders yup no this is great and it helps it helps engineers communicate progress to a sales team because the sales team is used to communicating things like quota and quota target and percent of quota hit yeah so help me understand how you're breaking this down i'm just going to screenshot your home page right so when you say like you have a couple things there's a progress bar there's velocity per week and there's scope remaining what do you set first like do you set a number of points per scope yeah so we we use the data that's already being leveraged in tools like jira for example so somebody's defined you know call it an epic right some body of work and they've either created a bunch of tasks inside of that or they've added story points that you know whatever process that they use and then what we've done is we've looked at your historical data to say when something like that materializes how does it typically go from start to finish and then we start tracking work against that and what we do is we look for deviations from that normal and normally it takes maybe a day to review code this one's taking four days to review code why is that right oh the code is really complicated it was rewritten a bunch of times seven people wrote it instead of one person so uh it's hard to review and each one of those has a historical factor that said last time something like this happened this thing got later and later or it got earlier and earlier and that gets worked into a forecasting model this machine learning algorithm that we developed that then predicts three things when do we think it's going to get delivered how is that date changing and how is the change changing so is it getting later faster is it getting earlier slower basically what we're trying to explain to folks is are we confident in what we're saying we're going to do or are we losing confidence what we're saying we're going to do because that second derivative explanation is how humans make decisions with each other tell me about pricing here you you're you're really clear on your pricing page everyone starts at 400 bucks a month but i imagine you're average like rpo is probably much higher than that what's the average customer or team paying you per month yeah so it's it's about the size of the company right so how big is the technology organization we call them contributors right the people that are working towards delivery so uh what we look at is kind of development teams starting around 20 30 developers and going up from there so simple math right uh we're looking at kind of 12k 30k 50k or like our typical starting bands per year yep oh per year okay well 12 oh oh it's 400 per year per month i was gonna say holy crap this gets big very quick if you've got a thousand people on one team paying 400 bucks a month that was a yearly price that was the yearly price i got it all right take me back to day one when did you launch the business so we started the business you could really call our genuine kickoff with techstars in austin q1 and 2018. so jeremy my co-founder and i we've been working together since 2008 straight through 13 years now so were you guys nice you just split 50 50 at the start you split 50 50 at the start it was oh nice sport time working together um and and we said let's uh let's kick this off and so we you know we incorporated the company just before that got into tech stars drove down to austin and uh and kicked this thing off right in january 2018. why austin why not i imagine there's a tech stars in raleigh right there wasn't a tech stars in raleigh at the time actually the tech stars in raleigh started a year later uh and it was in partnership with metlife we were deciding between uh austin and boulder actually and we looked at ourselves and said you know what are we really good at we're really good at product really good at engineering technology type stuff and so we wanted to go to a program that was shaped around go to market and the md in austin amos he's a real go to market guy and that's where we felt like we would gain the most and so we ended up going to austin um we met our first employee there hired him on our last day at techstars we um got our first first round of funding there uh with a with a really great partner and and we've actually have now a third of our team in austin um in in conjunction with raleigh well that's super cool okay so give me a little funding history here so you're not bootstrapped how much did you raise back right on day one in 2018 so tech stars you know it's the standard 100k 100k deal so in 2018 in total we raise about a million bucks uh as like our precede and then we've had subsequent rounds in 2019 and 2021 um of a seed in c2 so in all we raise about eight million dollars and tell me more the pre obviously it's a little data now because it's back in 2018 i mean today standard seed rounds i mean i've seen ones as small as five caps i've seen ones as high as like 50 caps on a convertible note like a safe it's been all over the place but back in 2018 what did you get like a one-on-five sort of deal yeah we what we typically saw on the market was like a three to five uh three to five cap on a seat you know that yep yep okay got it so maybe like a one on a force or a deal and i forget what was the standard tech stars deal back then how much equity was it was it seven percent it was uh six percent six yeah yeah have they changed that i don't think it's changed at all since since it started they've been they've been the same they've been they've actually been very consistent i know yc's switches around a little bit i think tech stars have been very consistent yeah do you compete with your friends that maybe went through reply to yc and just just to make sure that you made the right choice with the tech stars yeah it's actually cool we uh we had a bit of lineage there so there's a local program in north carolina called nc idea which funds um equity-free grants it's an economic development thing for startups and we went through that program and there was another company sitting next to us and they went through tech stars in austin the year before us and then we went through tech stars in austin on their recommendation and then we actually share an office with a company here that went through tech stars in austin a year later uh with our our recommendation so we've we've been able to really propagate this raleigh austin pipeline you've seen it all yeah you've seen it all that's very cool all right take me back to the first customer in 2018 where did you find him like can you name who it was do you remember yeah so the very first customer was actually a small company called farm shots um they're a satellite imaging company they ended up getting bought by a big agriculture company called syngenta and so in that time there was a there was a handful of these um seed stage ag tech satellite imaging companies and each one got bought by a...