Founder Interview
How Fyma Reached 10 Customers and 50 Paid Cameras at €200 Per Camera Per Month (Interview with CTO Taavi Tammiste)
- Interview Date
- November 4, 2021
- Interviewee
- Taavi TammisteCTO and Co-Founder
Company Metrics at Interview Time
Pricing (2021)
€200 per camera per month
Paid Cameras on Network (2021)
50
Customers (2021)
10
Team Size (2021)
12
Seed Round Raised
€1,550,000
Historical Snapshot
These numbers were reported by Taavi Tammiste during his interview with Nathan Latka recorded in November 2021 and are a historical snapshot, not current figures. See Fyma’s current numbers.
Key Takeaways
- 01Fyma charges €200 per camera per month with no integration fees
- 0250 paid cameras were live across 10 customers as of November 2021
- 03The average new customer onboards around 20 cameras on day one
- 04Queen Elizabeth Olympic Park in London is the one named reference, a UK pilot with about 30 cameras set up, separate from the 50 paid cameras
- 05Fyma raised a pre-seed round of 250K in 2019 and a seed round of €1,550,000 in 2020
- 06The company had zero paying customers exactly one year before the interview
- 07Team stood at 12 people, with 7 on the engineering and data science side
- 08Fyma was founded in 2019 and targets commercial real estate and out-of-home advertising verticals
- 09Sales cycles are long because the buyers are enterprise and commercial real estate, and the only churn so far has been two short-term projects that were always meant to be short-term
- 10The company built its own training datasets of over 200,000 to 300,000 images
Company Metrics at Time of Interview
| Metric | Value | Source |
|---|---|---|
| Year Founded | 2019 | Founder interview, Nov 2021 |
| Pricing Per Camera (2021) | €200 per camera per month | Founder interview, Nov 2021 |
| Paid Cameras on Network (2021) | 50 | Founder interview, Nov 2021 |
| Customers (2021) | 10 | Founder interview, Nov 2021 |
| Average Cameras Per New Customer (2021) | 20 | Founder interview, Nov 2021 |
| Team Size (2021) | 12 | Founder interview, Nov 2021 |
| Engineers (Software) (2021) | 4 | Founder interview, Nov 2021 |
| Data Scientists (2021) | 3 | Founder interview, Nov 2021 |
| Pre-Seed Round (2019) | 250K | Founder interview, Nov 2021 |
| Seed Round (2020) | €1,550,000 | Founder interview, Nov 2021 |
| Training Dataset Size (2021) | 200,000 to 300,000 images | Founder interview, Nov 2021 |
Growth Breakdown
Pricing and Traction
As of November 2021, Fyma had 50 paid cameras across 10 customers at a list price of €200 per camera per month. The founder cautioned that most of those cameras were still in pilot phase, so what Fyma actually collected was well below list price times camera count. The company had zero paying customers one year prior.
Customers
Fyma reported 10 paying customers at the time of the interview, with pilots ongoing across the UK including at Queen Elizabeth Olympic Park in London where 30 cameras were deployed. The average new customer onboards around 20 cameras on day one.
Team
The full-time team stood at 12 people, the majority being technical staff including 4 software engineers and 3 to 4 data scientists, plus data labelers. The company had recently begun investing more in sales and marketing.
Funding
Fyma raised a pre-seed round of 250K in 2019 and a seed round of €1,550,000 in 2020, with the seed capital directed primarily toward research and development, reducing GPU costs, testing verticals, and entering the UK market.
Growth Strategy
Niche Focus on Commercial Real Estate and Out-of-Home Advertising
Rather than trying to apply computer vision broadly, Fyma concentrated on two specific verticals where camera-based movement tracking had clear commercial value. This focus allowed the team to build a product that could be deployed in twenty seconds without custom development work.
No-Hardware, Camera-Agnostic Approach
Fyma differentiates by working with existing CCTV infrastructure rather than selling or requiring proprietary hardware. Customers simply connect their existing cameras to Fyma's AI platform, removing integration friction and lowering the barrier to adoption.
UK Market Entry and Pilot Programs
The company made a deliberate push into the UK market, running multiple pilots in London and surrounding areas. The Queen Elizabeth Olympic Park deployment served as a high-profile reference customer to build credibility with enterprise buyers.
Per-Camera SaaS Pricing Model
Charging €200 per camera per month gives customers flexibility to scale usage up or down based on their measurement needs, such as running short-term experiments or seasonal campaigns, while keeping the revenue model predictable for Fyma.
Proprietary Training Data as a Moat
Fyma built its own labeled datasets of over 200,000 to 300,000 images on top of open-source foundations, improving model accuracy over time and making the product harder to replicate as the dataset grows.
Best Quotes
“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 a couple of buttons and you start gathering data.”
“So right now we charge €200 per camera per month.”
“So right now, I think we're working with about 10 to 15 customers, 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 twenty twelve London Olympics were set up. So we have like 30 cameras set up there.”
“I think a year ago we were launching our first version of the web application, and we didn't have any paying customers.”
“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 €1,550,000 December last year.”
“I think at the moment, the entire team is around twelve, thirteen people. Most of it's 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.”
“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'll turn this into pedestrian street for the summer. Let's measure how traffic works there. That has happened on two occasions basically. So churn currently has only been for short term projects that were meant to be short term projects, but no one has actually churned from being a customer to not being a customer yet.”
“I think I wish I wish I knew at 20 that that university knowledge is not the same as real world knowledge.”
What Happened Next
This interview captured Fyma at an early stage in November 2021, when the company had just reached 10 paying customers and 50 cameras on its network following a seed raise of €1,550,000. The figures here are a point-in-time snapshot reported by co-founder and CTO Taavi Tammiste and do not reflect the company's current scale. Visit the Fyma company profile on GetLatka for the latest available data.
View Fyma’s current profile and metricsFull Transcript
Chapters
- 0:00Introduction and Product Overview
- 1:05How the Technology Works (No Hardware, Existing CCTV)
- 1:38Training Data and AI Models
- 2:06Pricing Model: Per Camera Per Month
- 3:42Average Customer Camera Count
- 4:07Founding Story and Origin in Tallinn
- 5:31Current Customers and UK Pilots
- 6:48Funding Rounds: Pre-Seed and Seed
- 8:13How the Valuation Was Set
- 9:02Co-Founder Karen Burns Is CEO
- 9:47Team Size and Composition
- 10:29Churn and Customer Retention
- 11:21Famous Five: Books, Tools, and Habits
Introduction and Product Overview
Nathan Latka
00:00Hey, folks. My guest today is Tavy Tamiste. He has a passion for finding actionable value using data all by applying machine learning. He's doing this building fyma dot ai right now. We're gonna jump in today. Again, no code AI computer vision tool. Tavy, you ready to take us to the top?
Taavi Tammiste
00:16>> Yeah. Of course. Thank you for having me, first of all.
Nathan Latka
00:18You bet. Okay. So it's a no code, again, AI computer vision software. Who who's paying for this, and how are they using it?
Taavi Tammiste
00:26>> So the idea basically got started that it's really difficult to build computer vision applications. Fyma by itself is currently targeted at commercial real estate developers, anybody who has physical environments that have movement in them that people need to track and also out of home 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
00:56>> we're tackling at the moment.
Nathan Latka
00:57And do they basically attach this to their cameras, right, the commercial real estate or the billboards to track metrics Yeah. Of people walking in front?
How the Technology Works (No Hardware, Existing CCTV)
Taavi Tammiste
01:05>> 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 a couple of buttons and you start gathering data.
Nathan Latka
01:26So, Tava, your software enables these cameras to recognize that's a pedestrian, that's a car, that's a male, that's a female. What dataset did you purchase to fuel and train your model, or are you built on something that's open source?
Training Data and AI Models
Taavi Tammiste
01:38>> So both basically we have our own data sets, we're gathering data ourselves as well. We did use open source data sets like COCO data sets to start, but a long way from that. So I think our data sets now are above 200,000, 300,000 images at the moment. So, it's growing by the day basically.
Pricing Model: Per Camera Per Month
Nathan Latka
02:06What does someone who owns a commercial shopping center, for example, pay you on average to use your technology each month?
Taavi Tammiste
02:12>> 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 it can vary from day to day as well. So at one point, you know, you have new COVID 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 wanna see business as usual and
02:34>> you pay for 10 cameras. So so it's it depends a lot actually on that.
Nathan Latka
02:38People are changing their billing every single day?
Taavi Tammiste
02:41>> 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
Nathan Latka
02:48SaaS tools. There's none of them where I go in and I upgrade and downgrade every single day based off a usage metric.
Taavi Tammiste
02:54>> Yeah. The thing with the commercial real estate is that they very often run to run experiments and measurements. So for example, think of it like this, I have, you know, a shopping center and 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 to fyma and measure something. So these types
03:18>> of experiments can be run. But yes, you are correct in the sense that most of the cameras we have are like 24/7 running at the moment.
Nathan Latka
03:25I see. So what do you charge per camera per month?
Taavi Tammiste
03:29>> So right now we charge €200 per camera per month.
Nathan Latka
03:32Okay. So call it $225 US dollars or something like that. And the average logo, the average brand that signs up for you, how much cameras do they onboard on day one?
Average Customer Camera Count
Taavi Tammiste
03:42>> So it depends. I think the last average I looked is around 20 cameras, but it can be one. It can be 50.
Nathan Latka
03:50Yep. So can we take I mean, again, I'm looking at a sweet spot here. 20 cameras, two hundred twenty
Taavi Tammiste
03:54>> Twenty five cameras. Is about is about
Nathan Latka
03:564,500 per month when a new brand signs up. Is that about right?
Taavi Tammiste
03:59>> Exactly.
Nathan Latka
04:00Yeah. That's correct. Give me the backstory here. How did you get the idea? When did you write the first line of code for this?
Founding Story and Origin in Tallinn
Taavi Tammiste
04:07>> 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've been working with large corporates and I've been trying to run my own AI consultancy business. 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 Tallinn, Estonia, where they wanted to measure cars on city streets
04:32>> 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. It So took six months to actually get something out of it. And now with fyma
04:56>> you can do it in twenty seconds basically. So the trouble of sort of building custom AI applications is where this pain got started from. Now it's a lot easier to do it basically. But there 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,
05:21>> look at everything.
Nathan Latka
05:22Yep. Okay. Interesting. I love the niche focus, commercial real estate makes a lot of sense to me. Talk to me about how many customers you're working with now today.
Current Customers and UK Pilots
Taavi Tammiste
05:31>> So right now, I think we're working with about 10 to 15 customers, 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 twenty twelve 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
05:59>> go ongoing. So we have a lot of traction that has sort of recently come up there.
Nathan Latka
06:04So, Tabby, last month, how many paid cameras were on your network?
Taavi Tammiste
06:08>> How many paid cameras? I think around 50.
Nathan Latka
06:11Around 50 total. Okay. Across 10 customers.
06:16Is that right? Yes. 50 across 10 customers? Okay. And and I mean so if we take 50 across 10 customers at 225 a camera, that means you guys are doing about $11,000 a month in revenue right now?
Taavi Tammiste
06:31>> 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.
Nathan Latka
06:38Okay. Got it. So about $6,000 a month in revenue, but still, everyone has to start from zero. So congrats on your first $6,000 a month. Now, have you bootstrapped all this or did you raise?
Funding Rounds: Pre-Seed and Seed
Taavi Tammiste
06:48>> 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 €1,550,000 December last year.
Nathan Latka
07:05Mhmm. And and walk me through, sir, what you use that money on.
Taavi Tammiste
07:11>> So basically, that money went into mainly into research and development, getting the cost down of the running the GPUs, running the machine learning models and the neural networks, testing out different verticals because we didn't start with commercial real estate. We started in various different ways where we saw a problem, but this is where we sort of ended up in our sweet spot. And then taking The UK market, that's been a big one as well. So entering
07:41>> that market.
Nathan Latka
07:42Mhmm. Very cool. Okay. So you raised the 1.5 and again, doing about $6,000 a month right now in revenue. What were you doing exactly a year ago? Do you remember?
Taavi Tammiste
07:51>> That's a good question. I think a year ago we were launching our first version of the web application, and we didn't have any paying customers.
Nathan Latka
08:01Got it. So zero back then. Nice. So interesting. So when you go out and raise the 1,500,000, but your pre revenue, how do you come up with the valuation to raise that?
How the Valuation Was Set
Taavi Tammiste
08:13>> Well, depends basically because we did have a very good idea. We did have an understanding of how the market worked and what the total market size would be in computer vision applications, how the consulting market would look like. We had a very good lead investor who helped us figure this out as well, to be honest. So they have helped us put together our valuation. So that's how it came together, basically.
Nathan Latka
08:38Mhmm. And so what valuation did you end up using?
Taavi Tammiste
08:43>> Don't quote me on this because I don't remember by heart, but I think it was around 5,000,000.
Nathan Latka
08:47Okay. And did that feel right to you or in the right range?
Taavi Tammiste
08:51>> I think it felt right in the stage we were at and and also in the sort of area we were at as well.
Nathan Latka
08:58Mhmm. And when you say we, did you have a co founder here?
Co-Founder Karen Burns Is CEO
Taavi Tammiste
09:02>> Yes, I do. I have a co founder called Karen Burns. So she's she's actually the CEO of the company and I'm the CTO.
Nathan Latka
09:08Did you guys split equity fifty fifty at the start? Yes. Okay. Got it. So so now it's what, like forty forty and then investors own 20%, something like that?
Taavi Tammiste
09:18>> Something like that. We don't really know the capital by heart, but Yeah.
Nathan Latka
09:22No, 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?
Taavi Tammiste
09:29>> Well, we have a pretty decent runway still to go. Depending So on when when we will raise and what we will raise, I can answer that question once we have a couple of projects end. Let's put it like this.
Nathan Latka
09:43Tell me more about your team. How many full time today?
Team Size and Composition
Taavi Tammiste
09:47>> I think at the moment, the entire team is around twelve, thirteen people. Most of it's 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 of that part.
Nathan Latka
10:09How many engineers?
Taavi Tammiste
10:12>> I think engineers so software, I think four, and data science, I think three or four also.
Nathan Latka
10:20Got it. So about seven there total on the engineering side. Nice. And then what about churn? Have you had anyone pay you and then stop paying you?
Churn and Customer Retention
Taavi Tammiste
10:29>> 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'll turn this into pedestrian street for the summer. Let's measure how traffic works there. That has happened on two occasions basically. So churn currently has only been for short term projects that were meant to be short term projects, but no one has actually churned from being a customer to
10:57>> 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, know, they're gathering data for a year, two years, ten years. And then the product actually gets better on the back end as well because it's a software product instead of
11:20>> a hardware product, right?
Famous Five: Books, Tools, and Habits
Nathan Latka
11:21Very cool. Hey, this makes a lot of sense. I love the story, Tavy. Let's wrap up with the famous five. Number one, what's your favorite book?
Taavi Tammiste
11:28>> What's my favorite book? Recently, my favorite book is actually President Obama's book. I really like that one.
Nathan Latka
11:35Number two, is there a CEO you're following or studying?
Taavi Tammiste
11:41>> No, there isn't. And I don't do this on purpose.
Nathan Latka
11:45Number three, what's your favorite online tool for building fyma?
Taavi Tammiste
11:49>> My favorite online tool for building fyma? Slack, definitely.
Nathan Latka
11:55Number four, how many hours of sleep do you get every night?
Taavi Tammiste
12:00>> Six.
Nathan Latka
12:01And what's your situation? Married, single, kids?
Taavi Tammiste
12:05>> In a relationship.
Nathan Latka
12:06K. Not married. Any kids?
Taavi Tammiste
12:09>> Nope.
Nathan Latka
12:09Okay. And how old are you, Tabby?
Taavi Tammiste
12:12>> I'm 32.
12:13>> 32.
Nathan Latka
12:14Last question. Something you wish you knew when you were 20.
Taavi Tammiste
12:18>> Something I wish I knew when I was 20.
12:26>> I think I wish I wish I knew at 20 that that university knowledge is not the same as real world knowledge.
Nathan Latka
12:34Guys, there you have it. Fyma 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 $6,000 a month in revenue as they look to scale. They did a $1,500,000 seed last round at a $5,000,000 valuation, now scaling with our team of 13, trying to move more
Taavi Tammiste
12:56>> of these pilots into paid customers.
Nathan Latka
12:58Tavi, thanks for taking us to the top.
Taavi Tammiste
13:00>> Thanks for having me.
Nathan Latka
13:02One more thing before you go. We have a brand new show every Thursday at 1PM Central. It's called Shark Tank for SaaS. 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 1PM
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