How Functionize CEO Tamas Cser grew Functionize to $17.3M revenue and 36 customers in 2024.

hello everyone my guest today is tomas chair since 2015 he's been building function eyes which has been delivering the first ai powered autonomous cloud-based testing platform to automate the painstaking process of testing web applications so moss you're ready to take us to the top absolutely ready to go all right so i mean should we think of this like kind of rainforest qa or sauce labs or kind of what space are you playing in here this is really the next generation automation platform if you think about rainforest or sauce labs it's traditionally either still really manual or very very script heavy what we're trying to do here is really take big data on computer vision and natural language processing and make testing truly the next generation aiml driven uh very very low human touch required um approach okay so i mean tell me a specific customer that right now has this deployed and how they're using it what cost savings have they had would they switch from absolutely so we see basically a couple of different scenarios where we see customers either dropping existing scripting solutions some that have dropped trained for us that we've taken yeah sorry can you give a really specific example like actually name the customer absolutely for example is a customer that we took they were a customer of rainforest and moved over to function eyes and have been successful ever since and and we're excited to have them as a customer certainly we see greenfield opportunities as well as as uh customers that have tried scripting such as salesforce what did so actually jay was just on the show uh four weeks ago he's obviously leading a nice turnaround there at zenefits but help me understand what they were able to save or get with you they couldn't get from rainforest do they have to have like less developers you know committing code or doing automated reviews or where do they save money or time or energy i think it's primarily speed it's expertise required and the overall effort involved basically to get automation in place okay so are you making testers more efficient or are you replacing them uh we don't necessarily replace testers what we see generally in a deployment is customers generally struggle for expertise so people generally just get more productive there's not enough coverage in place so they get to do more coverage more work more productivity faster time to market i mean most developers who i've interviewed in this space the biggest issue is is actually making sure you write all the tests so you have full coverage on critical pieces of the application and a gap in a test or a test that breaks or things like this this obviously then makes things not work so well so are you essentially plugging those gaps helping make sure those things do not happen absolutely so we plug the gap coverage we got plug the gaps and maintain ability so as testing scales out it's a huge challenge to keep that up today and those are the main key challenges that we help our customers uh you know basically as you were saying plug those gaps okay and now what's your model are you pure play sas or professional services plus sas or something else we're a pure sas model primarily we see some demand certainly around professional services we we have done some of these but we're looking at partners um to to take that burden if you will we're primarily focused on product okay and i mean give me a general sense here i see your pricing you have a lot of different kind of cohorts we don't have time to talk about all of them but on average what's the sweet spot what's the customer going to pay you per month for your tech so we're looking starting at around 5k we're primarily focused mid-market to enterprise and we really are a high value high impact type of product where um we really don't come in and don't start playing unless there's a a serious business problem to solve okay so all customers basically paying five north of five grand a month you know call it sixty thousand dollar acvs right now that is our sweet spot and that's what we're focused on you know i think is as we mature as a company nice product certainly other type of models i think something that we're talking about considering but right now that is absolutely the sweet spot and what we're focused on when you look at your historical pricing experiments though did you did you did you move down market or up mark in other words you know is that 5000 grand a month is that a fair average across your current paying base or a bunch of them on cheaper plans because of early pricing tests to be perfectly honest last year we were starting at 10k so this has been a drop but i think in the previous years we started much much much lower so this is really a question of maturity and as the as the company evolves us finding the right one so we kind of started much lower and then move much higher and kind of are now coming down and and as we find more productivity in our product and we understand our customer base and getting more efficient in deployments we can we can start introducing lower tier pricing and make that successful when did you guys write your first line of code for the mvp oh boy that's probably uh early 2014. okay and how much did you guys you and your co-founder sink into kind of product development uh before your first dollar revenue you know we were probably two to three years in before our first revenue can you quantify that i mean are you talking like a million dollars into the platform before revenue or that's a great question um it's it's slightly difficult to quantify because it was spun out of you know i primarily did a lot of development myself and spun out of a previous company that was successfully running with cash flow positive and that i ran for about you know over 10 years and with the development and it kind of started you know leveraging existing resources there was not really a solid dollar amount assigned to that and it really started as a you know as a pet project to solve our own internal problems if you ignore your sweat equity though imagine maybe you paid some developers uh contractors designers folks like that can you try and quantify what that counts it's millions of dollars for sure sunk in before we saw the initial dollar start returning so you're really rich or you raise capital on day one um cash flow positive company successful previous company that that enabled me to dabble and take the company and bootstrap it to quite far and then we once we had a working product and we saw our early beta customers all you know we charged always charged something sorry charging i think 500 bucks per customer early on and then then we were able to raise friends and family around and then from there things kind of took off organically and how much today have you raised all in uh we just want 60 million all in one six or six zero yep one six one six okay and i mean why did you like i mean you don't raise unless you have to because you get deluded right why did you absolutely have to take that dilution why couldn't you keep bootstrapping this with your own money i think it primarily comes down to you know what the company do you want to build and market conditions so i think that this is a huge market with a huge opportunity and when i was considering the you know razer not race question that i think is is on the mind of a lot of founders it it was very clear to me that the market opportunity and the timing meant that we have to move quickly and what the capital is allowing us to do is just to move and do that you know faster more iterations and and more basically trial and errors that are faster so um i think time to market for us and really the sweet spot solution and land grab i think is worth worth the uh the dilution if you will and i mean you've done this before you had a successful company since like prior to this so you understand cash management when you talk about being aggressive i always like to understand what amount of burn comfortable founders are comfortable sleeping with at night so you've you've brought in 16 you're scaling the company i mean are you cool with like 100 grand burn or a million burn per month where do you kind of trying to optimize that i think like like every other company in silicon valley we're looking at probably uh 18 to 24 months runway where we are very focused and very specific milestone that we want to reach if we reach those milestones we're comfortable increasing the burn and and also going after opportunity so we see a lot of opportunity and that's across the board and for that i think we are a little bit more aggressive than we initially thought and that's across the board i think customers partner opportunities and and again just if you look at the market horizontally so um it's a very difficult question i think what is the right amount of burn and something that you know we're adjusting as we go so just to be clear you're saying when you think about raising based off your historic expertise you like to raise for between 18 and 24 months of runway yeah i think that i think that's something that that works pretty well i think you adjust things do not turn out the way that you imagine i think that conditions change very quickly i i kind of feel like every three months the company is a new company and conditions change and yeah i guess that's what i'm asking though is like again you're trying to be aggressive you raise the series a on march 5th 2019 for for 16 million dollars right if you and your pro formas and your deck are saying this is going to cover 18 months of runway you basically have a forecast that takes you up to almost 800 grand a month and burn i'm...