Fyma Revenue, Valuation & Funding (2024)

hey folks my guest today is dave damiste he has a passion for finding actionable value using data uh all by applying machine learning he's doing this building fima dot ai right now we're gonna jump in today again no code ai computer vision tool tabby are you ready to take us to the top yeah of course thank you for having me first of all you bet okay so it's a no code again ai computer vision software who's paying for this and how are they using it so the idea basically got started that it's really difficult to build computer vision applications um fiber by itself is is currently targeted at the commercial real estate developers anybody who has physical environments uh that have movement in them that people need to track and also out of our advertising companies so people who have billboards people who want to understand what's going on their billboards but the technology itself has potential to be used everywhere but that's the first two verticals that we're tackling at the moment and do they basically attach this to their cameras right the commercial real estate or the billboards to track metrics yeah people walking in front that's that's the that's the idea basically so we're one of the first companies out there who doesn't deal in any hardware we take your existing cctv cameras push the stream to our ai brain and give you data out and it really is as simple as that and there's no integration fees there's no nothing you just press couple of buttons and you start gathering data so toby your software enables these cameras to recognize that's a pedestrian that's a car that's a male that's a female what data set did you purchase to fuel and train your model or are you built on something that's open source so both basically we uh we have our own data sets so we're gathering data ourselves as well uh we did use uh open source uh data sets like cocoa data sets to to start but we're we're a long way from that so i think our data sets now are above 200 000 300 000 images at the moment so yeah it's growing growing by the day basically what does someone who owns a commercial shopping center for example pay you on average to use your technology each month it depends because because the solution is so easy to use we charge per month per camera so it depends on how many cameras they want to look at and yeah and it can vary from day to day as well so at one point you know you you have new covet restrictions or whatever and you want to measure everything so you know you pay for 50 cameras and the other day you know you just want to see business as usual and you pay for 10 cameras so so it's it depends a lot actually people are changing their ceiling every single day well it's it's a software as a service so you can do that you can click you know i use a bunch of i use a bunch of sas tools there is none of them where i go in and i upgrade and downgrade every single day based off a usage metric yeah the thing with the commercial real estate is that they very often want to run experiments in measurements so for example think of it like this i have you know a shopping center i have a parking lot outside my idea is i'm going to order 10 food trucks there and i want to see what happens for those 10 food trucks i'm going to take 10 cameras outside attach them to 5 and measure something so these types of experiments can be run but yes you are correct in the sense that most of the cameras we are are like 24 7 running at the moment i see so what do you charge per camera per month so right now we charge 200 euros per camera per month okay so you call it 225 us dollars or something like that and the average logo the average brand that signs up for you how much cameras is the onboard on day one so it depends um i think the last average i looked is around 20 cameras uh but it can be one it can be 50. yep so can we take i mean again i'm looking at a sweet spot here 20 cameras 225 is about is about 4 500 per month when a new brand signs up is that about right exactly okay interesting give me the back story here how did you get the idea when did you write the first line of code for this so we got started around two years ago and i was i've been working with applied machine learning for about eight years now and i i've been working with large corporates and i've been trying to run my own ai consultancy business and this this idea actually got started from when i was sort of bootstrapping my own ai consultancy business and we were doing a project for a city here in thailand estonia where they wanted to measure cars and city streets basically sounds easy enough right but what ended up happening was that that project from start to finish took six months so we had to find data science resources we had to gather the data we had to train the model we had to put that model to run on some infrastructure somewhere and then we had to visualize the data with some software so it took six months to actually get something out of it and now with fiber you can do it in 20 seconds basically so the trouble of sort of building custom ai ai applications is where this pain got started from now it's a lot easier to do it basically but there is a there is a very important part in this is that you can only do it in a specific niche and in computer vision we're doing it in the cctv camera angle because you can at least not yet make an ai algorithm that can you know look at everything yep okay interesting i love the niche focus commercial real estate makes a lot of sense to me um talk to me about how many customers you're working with now today so right now uh i think we're working with about 10 to 15 customers uh but we are running a bunch of pilots in the uk at the moment so the customers we can talk about is the queen elizabeth park area in london in the upper east side of london that's where the 2012 london olympics were set up so we have like 30 cameras set up there and yeah basically inside london outside london in exhibition centers trials are go ongoing so we have a lot of traction that has sort of recently come up there so toby last month how many paid cameras were on your network how many paid cameras i think around 50. around 50 total okay across 10 customers is that right yes 50 across 10 customers okay and i mean so if we take 50 across 10 customers at 225 a camera that means you guys are doing about 11 000 bucks a month in revenue right now not that much because the thing is that most of these are still in pilot phase so we're doing around half that i think okay got it so about six thousand dollars a month in revenue but still yeah everyone has to start from zero so congrats on your first six a month now have you bootstrapped all this or did you raise no we have raised two rounds so we raised our pre-seed round of 250k i think in 2019 and we raised a seed round of 1.55 million euros december last year and and walk me through sort of what you use that money on so basically that money went into mainly into preseason development getting the cost down of the running the gpus running the machine learning models and the neural networks uh testing out different verticals because we didn't start with with commercial real estate we started in various different ways where we saw a problem but this is where we sort of ended up as in our sweet spot and then taking the uk market that's been a big one as well so entering that market very cool okay so you raised the 1.5 and again you're doing about 6 000 a month right now in revenue what were you doing exactly a year ago do you remember that's a good question i think a year ago we were launching our first version of the the web application and we didn't have any paying customers got it so zero back then nice so interesting so when you go out and raise the 1.5 million but your pre-revenue how do you come up with the valuation to raise at um well it depends basically because we did have a a very good idea we did have an understanding of how the market work and what the total market size would be in computer vision applications uh how the consulting work consulting market would look like we had a very good lead investor who helped us figure this out as well to be honest uh so they have helped us put together our valuation so so that's how it came together basically and so what valuation did you end up using don't quote me on this because i don't remember my heart but i think it was around 5 million okay and did that feel right to you or in the right range i think it felt right in the stage we were at and and also in the sort of area we were at as well and when you say we did you have a co-founder here yes i do i have a co-founder called karen burns so she's actually the ceo of the company i'm the cto did you guys split equity 50 50 at the start yes okay got it so so now it's what like 40 40 and then investors own 20 something like that something like that we don't really know the capital by heart but yeah no no no just curious now you've had some growth i mean you've grown revenue since your last round are you planning on raising anytime soon uh well we have a pretty decent runway still to go so depending on when uh when we will race and what we will raise um i can answer that question once we have a couple of projects end yeah let's put it like this tell me more about your team how many full time today i think at the moment the entire team is around 12 13 people most of its technical team we've recently been putting a lot of effort into sales and marketing as well because we see that's a big part of how you get the name out there but yeah most of it's basically software development data scientists data labelers you know all that part how many engineers uh i think engineers so software i think for and data science i think three or four also got it so about seven they're total on the engineering side nice and then what about churn have you had anyone pay you and then stop paying you uh yes but only for short-term customers who came in as short-term projects so we have customers like hey i'm turning this street that's usually meant for cars we're turning this into pedestrian street for the summer let's measure how traffic works there that has happened on two occasions basically so so churn currently has uh has only been for you know short-term projects that were meant to be short-term projects uh but no one has actually churned from being a customer to not being a customer yet and the thing with this is that while our sales cycles tend to be pretty long because it's you know enterprise sales and it's you know commercial real estate once a customer comes with us they really don't have a reason to leave because you know they're gathering data for a year two years ten years uh and then and this the product actually gets better on the back end as well because it's it's a software product instead of a hardware product right very cool hey this makes a lot of sense i love the story toby let's wrap up with the famous five number one what's your favorite book what's my favorite book uh recently my favorite book is actually president obama's book i really like that one number two is there a ceo you're following or studying um no there isn't and i i don't do this on purpose number three what's your favorite online tool for building ima my favorite online tool for building fima slack definitely number four how many hours i sleep to eat every night six and what's your situation married single kids uh in a relationship okay not married any kids nope okay and how old are you toby i'm 32 32 last question something you wish you knew when you were 20 something i wish i was 20. [Music] um i think i wish i wish you know at 20 that uh that university knowledge is not the same as real world knowledge guys there you have it fima launched back in 2019 they're helping folks like malls or folks that look at traffic patterns use cameras to understand where pedestrians are where cars are run estimates and experiments they were doing no revenue exactly a year ago now doing about six thousand dollars a month in revenue as they look to scale they did a 1.5 million dollar seed last round at a 5 million evaluation now scaling with our team of 13 trying to move more of these pilots into paid customers toby thanks for taking us to the top thanks for having me one more thing before you go we have a brand new show every thursday at 1 pm 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 arpu 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 pm central additionally remember these recorded founder interviews go live we release them here on youtube every day at 2 p.m central to make sure you don't miss any of that make sure you click the subscribe button below here on youtube the 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 counter them and know that i appreciate your guys's support all right i'll be in the comments see ya