Ep. #1064 - Creating Intelligence from Video

Matt Watson 0:00
And we’re back for another episode of the Startup Hustle. This is your host today, Matt Watson, excited to be joined today by Sud Bhatija. He is one of the co-founders and Head of Growth of Spot AI. Learn more about his company today and his journey of being an entrepreneur. Before we get started, I do want to remind everybody that today’s episode of Startup Hustle is powered by FullScale.io. Hiring software developers is difficult. Full Scale can help you build a software team quickly and affordably and has the platform to help you manage that team. Visit FullScale.io to learn more. Sud, welcome to the show, man.

Sud Bhatija 0:32
Thank you for having me, man. I’m excited.

Matt Watson 0:34
So tell us a little more about your company. And what you guys do, it looks like all has to do with security and video and all kinds of cool stuff. Tell us tell us more about your company,

Sud Bhatija 0:44
for sure. So what’s been happening over the last seven or eight years in business is that the number of security cameras has actually been increasing a whole lot. There are a billion security cameras in the world. And that’s about double what it was just about six or seven years ago. And if you typically run a larger, multi-location business, which has people, vehicles, and things moving around, visual context is very valuable to solving problems. You can’t be everywhere at the same time. And sometimes you just need to see what’s going on. So this increase in cameras has been driven by business owners of all scales, using their camera systems for, of course, security, but also to make better decisions about their business and run their businesses better. And if you think about it, video data is about two-thirds of business data. It’s because it’s really heavy. And it’s pretty dense, a lot of data, a lot of data, a lot of data, a lot of data. And if you look at the startups, the last like, you know, 1520 30 years, a lot of it, you know, the whole movement on business intelligence has been focused on unstructured data, structured data. Now, what we’re doing is actually helping businesses tap into that unstructured data to get insights about what’s happening in their businesses, make better decisions and make more money or save more

Matt Watson 2:15
costs. So what So what gave you guys the original idea to do this? Where did the original idea come from?

Sud Bhatija 2:22
So I met my co founders, when we were all classrooms at Stanford. And one of the, you know, around that time companies like nest and ring, were becoming a really big deal. You know, Nest got acquired for money soldering, and, you know, everybody we knew was buying those. And the question that came up for us was, if you really want to look at your $100, Amazon package on your front doorstep, why don’t you want to look at your $100,000 machine on your factories, right. And it was his hypothesis that businesses were using, we’re also need to use video because video is so valuable. And that’s really what got us starting, you know, started talking to customers. And what we realized is that the same behavior change that was happening in the consumer world was also happening in the business where people were looking to use their cameras for different purposes. And the number of cameras is growing really, really fast. But the problem was that I didn’t have the right software to actually be able to use it.

Matt Watson 3:27
I mean, historically, lots of businesses have had security cameras, right? But it’s like, hey, somebody robbed the bank, let’s go back. And, you know, look at the VCR footage and figure out, you know, who the criminals were, right? Like, people didn’t really use the cameras like very proactively for anything, they were just weird situations like that. Otherwise, they wouldn’t really use for anything.

Sud Bhatija 3:48
That’s exactly right. And as a result of this, the software wasn’t built for that the software was built for, you know, this, it was built to be used once in six months. Yeah, and a lot of software features that you and I would assume, would exist everywhere, right? Like, let’s say you’re looking at YouTube, and you’re able to seek and scroll the video to like, scroll to wherever you want to in the video, or, you know, shattered video with the link. And all those things didn’t exist in the business world that much. Because a lot of the companies they you know, at that point, the value of the technology wasn’t the hardware, the bitcode hardware, but they didn’t build the software.

Matt Watson 4:28
What do you think part of that was because of just the challenges of dealing with all that data? I mean, you go back 1015 20 years ago, I mean, first of all, we didn’t even have like 10 ADP and high definition and things like that either. So the video quality was very good. But then also just the sheer volume of data you’re talking about from hundreds 1000s of cameras, like it wasn’t really conceivable to even build software to process all of that stuff like the processing power needed was didn’t exist either. I don’t think

Sud Bhatija 4:56
that’s exactly right. And what’s been happening over the last I said decade is, as we’ve gotten to this, you know, the most, you know, the more recent and what’s now fairly clear with the golden age of AI, is these AI specific silicon chips have been developing at a very, very fast clip. So, you know, Moore’s Law slowed down, but then companies are developing GPUs and GPUs, which were specific for AI. Yeah. And what is what has been happening every year is the cost for, you know, unit compute has been going down significantly or near. So this for the same cost, you can get a chip that’s like, you know, several times more powerful than the one that you’re before. And what that allows us to do is actually crunch all that video data, right where it’s created. And it gives you the, you know, what the actual horsepower but also at a practical cost to be

Matt Watson 6:01
able to do it. So the the other term for that is edge computing, right? So, you, you see this in all forms of like IOT devices, the Internet of Things, devices, all these things, is to be able to push this sort of compute all the way to the edge. So that way, you don’t have to upload all these videos and process process them somewhere, you can actually do this processing on the edge, which saves a lot of bandwidth and cost and computational costs, all this kind of stuff, because you can do it on the device like that. That is like one of the big innovations that it took to get here I believe,

Sud Bhatija 6:33
exactly. And, and the reason that’s really relevant for video is because video is so heavy, moving video to the cloud is both, you know, hard, or it’s both impractical and expensive. Yep, it’s difficult on your bandwidth. And once you get into the cloud, it’s really expensive to store and process

Matt Watson 6:52
1000s of servers, it would take the process at all, exactly that

Sud Bhatija 6:56
it’s much more expensive. So you’re now able to store it on a local hard disk. And you’re also able to process it with a much cheaper chip, that unlocks a lot more value at a price point that actually makes sense for the market. And that trend came together with, you know, us seeing this behavior change. And that’s basically what led to starting the company.

Matt Watson 7:21
So for your guys’s solution, what was what was the original idea was originally idea to help, like, detect, like, oh, somebody is, you know, at your facility, and it’s three in the morning, and we’re gonna alert you? Or was it like, health and safety things? Or, you know, like it was a certain like a use case that you were after? Or was it like, hey, we want to do all of these use cases?

Sud Bhatija 7:43
That’s a great question. So actually, we started off in a different form. And this is our journey as entrepreneurs find the right product form to to fit the market, we actually started off thinking will be a smart camera company. And what we were focused on for these different businesses were these operational use cases directly. And, you know, you’re gonna identify those and we’ve spent, you know, over the years plus kind of figured out different types of businesses, and what were the operating challenges that they want to solve? And what could video help solve for them. What we realized after we spoke to a lot of customers was a customers were like, Hey, this is great, but I don’t want to change my cameras. So hey, you know, how do I do that, too, is, you know, you’re talking about all these things that I want to do someday, but today, I can’t access and see my video and use it like?

Matt Watson 8:41
Definitely, were you also trying to sell the cameras. Also,

Sud Bhatija 8:45
at that point, we were focused on only being a camera system, like like only selling smart cameras. So you’re selling the hardware to exactly you’re asking them to replace their cameras. Yeah. Then what we realized then was the value that customers foresee was, like, had to be entirely software based. And we had to build a software only solution, because they already had a bunch of these existing cameras that were just too expensive and too cumbersome to remove. And the second thing is that a lot of basic problems that we assumed were saw run again, this is our journey as founders, you realize that a very basic problem that customers like, you know, you thought was already solved, was actually not being solved. You know, the best ideas are the ones that are very obvious that it’s like, Hey, why is this not being done yet? And that’s what we stumbled into. And what we then decided is, we still build a camera system, but it will be focused on something that would work with what they already had. They wanted more cameras, we give them away for free. Because the value is not in the cameras. The camera is a sensor. The camera is producing data for you that you can utilize. The value is in the software, and the ability to use that data to then create a business outcome. So it became a much more software centric approach to it. Where we basically get the hardware for free and we work with whatever system stupid

Matt Watson 10:07
already. Well, that’s incredible. You give away the cameras for free. I mean, obviously, there must be an annual, you know, fee or whatever. And that’s it, you guys recoup your, your expense. But I, but I think one of the really key things here I would imagine, is you could, let’s say you go to like a department store somebody, right, and you might have like, 100 cameras already, the idea of them replacing those cameras, the probably the cost of the labor to replace the cameras is more than the cost of the camera itself, right? Like, there’s so much labor involved, and just like doing all of the work, and I can definitely see like, nobody wants to replace them. Nobody wants to deal with any of it.

Sud Bhatija 10:42
Absolutely. I mean, if you look at the cost of a camera system, the physical cost of the camera is actually much smaller compared to the cost of the installation. Right? Yeah. In most cases, so that’s exactly right. And, you know, if you offer them a solution that can work with what they have, and then can give them observability, on what’s actually happening with their camera system with the ability to then easily switch out cameras that are not working, when they actually have to do it. Is that very, very valuable to customers?

Matt Watson 11:13
So what So so as you guys made that pivot to just doing the software part of it, that created its own challenges of how you integrate with all these existing hardware platforms? Or was there enough standards around the video that was easy to integrate with all the existing camera systems that that exist out there?

Sud Bhatija 11:32
There were standards around video. So cameras use this user’s protocol called RTSP. And 95% of cameras user, as long as you’re an IP camera, you probably use RTSP. So we were able to leverage that, which definitely made things simpler. There were other challenges, obviously, which we as a business had to solve from a technology perspective is, irrespective of the type of cameras and the type of network, how do you make video reliably a pure glass to glass? So, you know, show it’s getting captured in the camera? How do you make sure that easily like like that reliably, and with low latency can be viewed from any device anywhere, right? It is effective of everything in the middle?

Matt Watson 12:16
Did you still have to provide them some kind of hardware to install, like on premise to connect to those cameras,

Sud Bhatija 12:21
we’d give them an appliance, which basically you do, again, play and record on the same network, which ordered record all those cameras. So you didn’t have to change cameras, but you had to install like a, like an appliance which

Matt Watson 12:33
configure the IP addresses or whatever. And

Sud Bhatija 12:35
actually, the system does all that for you. So the interesting part is, as you’re finding product market fit COVID hit us. So one of the things that we had to do early on, and you know, eventually we were done anyway, but it really accelerated that timeline is being able to remotely install devices. Well,

Matt Watson 12:53
and actually, I would imagine COVID would have helped you because a lot of a lot more companies needed cameras, because their buildings were empty and stuff, right, like, wood, wood. Did COVID actually help you from that perspective, too?

Sud Bhatija 13:05
It did, because I think one is businesses, you couldn’t have people on location. So businesses wanted to monitor what was going on. So that was one factor. That is as people came back to office people wanted to figure out are, you know, are? Is everybody following six feet distance protocols? And then, you know, a bunch of companies just wanted to rehaul like, their infrastructure, because they it was easier when nobody was allowed. Yeah, sure. So there are a lot of benefits, I think, then the flip side is we had to make sure the systems were really easy to install. And, you know, we had these early customers where they would have to coordinate with some team in the company to know when they could physically go to an office. So we had to make sure that they could go and they could plug it in and walk out and and work.

Matt Watson 13:56
Yeah, one of my nephew’s during COVID His job was to do security. And he just walked around an empty building all day and lat and just did laps around the building. It was just security. And there was nobody in the building because it COVID but somebody had to be there just to make sure you know, there wasn’t somebody doing some grazing, whatever. Yeah, interesting dynamics from all the COVID time, but I imagine is, you know, somebody having being in the surveillance security kind of solution. Like there had to be a lot of demand for it. So

Sud Bhatija 14:23
yeah, in fact, there were, I mean, unfortunately, there were different geographies and areas where crime was actually going up. And that was also leading to business owners wanting to secure the facility.

Matt Watson 14:35
Yeah, because the employees aren’t even there. So what So what other kinds of use cases do people use your system for? Like so for example, could like a department store use it and know like, Okay, how many people walk them down this aisle or like traffic patterns, like, safety stuff? Like where’s the jackhammer? You know, on the construction site, like what what kind of different use cases do people use it for

Sud Bhatija 14:57
there was a bunch of things, so you know, or the last Few years we have sold to customers across 17 different verticals. And, you know, at the end of the day, everybody buys a camera. The the, I’ll talk a bit about the use cases, at a basic level, what all businesses use camera systems for, in some capacities, incident resolution, something happened, we need to go and look for video, it could be a safety incident, it could be a theft, it could be a customer complaint, whatever have you. Looking for video is actually pretty difficult. So like I get it, all the features that you and I take for granted in you know, internet first world is, aren’t aren’t available to all these customers in with the systems they have. So if you have to look at six hours of video footage, you very often have to look through six hours of video footage for six hours. So we make that process really, really simple and make it very easy to collaborate. Like where we are we have we had customers where they were actually downloading video footage on spend drives and actually sharing it with other customers and or like with with law enforcement agencies or whatever have you. That’s a very cumbersome process, we allow them to like to do it securely with links. And then we allow them to collaborate with multiple people internally and externally on a single platform, instead of sending, you know a bunch of different emails and texts and have it all be in one place. So that’s kind of the basic use case. The higher order use cases depend on the kind of business but they really span two things they stand, you know, efficiency, safety and customer experience. So one vertical that we spend more time with is car washes. car washes, you know, once you buy an installer, carwash, how much money you make is this, depending on how many cars you can wash, the marginal cost of washing a car is relatively low. So what business owners are trying to do is maximize the throughput of those car washes. So what they’re gonna understand is, how long is the car taking to go through the process? How many cars? am I watching every day? Where in the process? Are they getting stuck? So we are able to give them a lot of analytics around that. Where you know, they can then define zones where they want to sort of pay attention to and the thresholds that they want to monitor where cars pass through, and understand how long they take cars to get from threshold A to B to C? And then how does that compare across all the locations? And are people getting stuck somewhere. So that’s sort of throughput and like an efficiency something

Matt Watson 17:34
that you like turning in an analytics, you’re taking video data, looking for key events that happen and then turning that into analytics and then turning that into dashboards and alerting things like that.

Sud Bhatija 17:46
Exactly other than or equal and things for, you know, vet houses which get a lot of our, you know, how many packages can you move, throw that out in a given day, that are you know, equal and things for manufacturing facility where you want to make sure that certain areas are are staffed at least a minimum amount, and at most a certain amount. So there are a bunch of efficiency use cases, on the safety side, you know, bad things happen in businesses. So, you know, what business was kind of figured out is other people in places they shouldn’t be. Other, you know, is that a surge or more than a certain number during a certain amount of time that we need to be aware of? Our Did you have a slip and fall are the forklifts and you know, people in a in a warehousing facility kind of getting very close to each other or moving our forklift moving too fast to a facility which allow the speed limit and therefore might cause an accident. So there are a lot that we can help businesses with. So

Matt Watson 18:43
all those kinds of different scenarios did. Did you guys have to use like computer vision and machine learning to specifically look for all those different scenarios? Or are the customers able to somehow like create some of their own scenarios on their own, or they have to go to you and say, hey, please, like create these scenarios.

Sud Bhatija 19:01
So what we do is we use VB leverage computer vision and machine learning to be able to, like, index and analyze the video. And what we then do is we based on the vertical and what the customer needs, we’re able to package it up into pieces or like into analytics that actually makes sense for the customer. It’s very easy to give a customer you know, a random, you know, data point or account or like, you know, all the supports in here. What’s but that’s not very often useful to them. What’s really useful is how does it fit into that workflow? How do you get that data to the right level of abstraction and accuracy that allows them to make a decision based on and that’s where we focused on doing

Matt Watson 19:48
the you guys are my back to my question, though, as it sounds like you guys have to like code for those like industry specific solutions.

Sud Bhatija 19:56
Yeah, and you know, we build things that are pretty horizontal across industries and In a lot of the foundations of the primitives are entirely horizontal across industries. And there are, you know, some specific outcomes that might be more industry specific. And we do that based on the markets that are targeting these people and what customers are asking us for.

Matt Watson 20:14
Well, before we continue on, do I remind everybody that finding expert software developers doesn’t have to be difficult, especially when you visit full scale.io, where you can build a software team quickly and affordably use the Full Scale platform to define your technical needs, and then see what developers are available to join your team visit full scale.io to learn more. So this appliance that you built, the day install, it does a lot of the kind of processing for you at the edge. But do you guys still end up storing a crap ton of video data, like on your servers to like, ultimately,

Sud Bhatija 20:46
actually know the video, unless the customer wants the video to be in the cloud, it’s not at the cloud.

Matt Watson 20:54
So you’re just pulling the analytics out of it,

Sud Bhatija 20:56
basically. And the basic idea is that it’s your video, it’s, you know, we want it to be private, we call it private by design, and you have to decide if you want the video to be backed up in the cloud, okay, you will have to allow a support person to look into your appliance to you know, solve a problem.

Matt Watson 21:18
So you know, so you don’t necessarily expect people to log into your software and like, look at the video feeds, they’re more looking at the events that came out of it.

Sud Bhatija 21:26
But actually both, but that’s the interesting part of the technology, they log into the software to look at the video feed, but the video is actually entirely sort of solved from the edge. Okay, so the video actually never leaves the cover the customers premise now. But the beauty of the technology is that they can still access it and use it anywhere.

Matt Watson 21:45
Okay, we can look so the looks like so your software may be connecting directly to their local camera or connecting your appliance or wherever they store the data. And

Sud Bhatija 21:54
that’s exactly right. Okay, very cool.

Matt Watson 21:56
Very cool. I like it.

Sud Bhatija 21:58
It’s a one of the clouds, it feels like the cloud, but it’s actually not.

Matt Watson 22:03
I don’t know if any, I don’t know if, you know, there is no cloud actually, right. Like, it’s just, it’s just somebody else’s server in a warehouse, basically, somewhere. Not really a cloud, you know,

Sud Bhatija 22:17
it’s the edge. And we know what what that allows you to do. And the beauty of it is that you can do all those things and still give the customer a very seamless and powerful experience. Yeah, from a data security perspective. Exactly. From a security perspective, or convenience perspective, you don’t need a VPN you don’t like, I like to log into some the, you know, some IP address, you don’t need some, like, you know, separate password for every site. It’s basically something that, you know, so access from your from a browser.

Matt Watson 22:47
So things that sound simple, like that are usually really, really freaking complicated behind the scenes, right? So, so tell us about some of those complexities that you guys had to deal with of like, okay, how do we architect and engineer this thing? Like, what were some of the big challenges you had? And?

Sud Bhatija 23:05
I mean, it’s, you’re absolutely right, it is very much. If they look simple, it’s actually a lot of work. And, I mean, before I go to that, but at a philosophical level, that’s what you know, as a business, as founders, we believe very strongly is it’s our job as a company to solve the Hustlers hardest problems and give it to a customer in a very easy to use experience. That’s the that’s, that’s our job. And that’s why we have a business is because that stuff is hard. And, you know, we build a team that is that’s worthless, invisible to execute on.

I’m not the technical guy on the team. But I will say that the there are a bunch of different challenges in terms of

I mean, firstly, cameras are, like very even though there is a streaming standard. That’s not always as, you know, a nice as it’s set up to be. network topology is a very interesting problem. You know, customers have different networks set up in different ways. You know, some networks are air gapped, they have different like, you know, VLANs. So just, there’s just a lot of complexity there that we have to we have to abstract. And if you’re trying to give the customer a really good experience, that all has to be invisible to them. All the things that you typically do as an IT person, we want all that to be bootstrapped into software. So that a lot of those like complexities that as a person, it’s hard enough to navigate, but I have to get software to do it. So network topology is a very interesting one. Network variability network uplink and downlink does interesting problem. How do you then make sure that the video is still available at a certain quality and doesn’t have enough doesn’t have latency? So that you’re actually looking at video that’s not like, near real time, in real time. So those are the challenges that we’ve had to solve at other levels.

Matt Watson 24:52
Were there any of those challenges that you know over the last few years like Man, this is a big one and we don’t know what we’re gonna do or didn’t know? Almost insolvent, or like, were there any, in particular challenges? Are they just like we just had to figure them out? Are there any that were overly difficult?

Sud Bhatija 25:08
I mean, I think I think a lot of these were particularly difficult given that the number of cameras on our platform has been increasing quite dramatically, because we’ve been experiencing dramatic growth. So you’re, so you’re not just you’re not, you don’t just have to solve these problems once, right, you also have to keep solving them repeatedly as you go to the next level of scale. Thinking one two years ahead on scale, and architecting, your your technology to then be able to, you know, go through that, and to to be able to support that. And then the other interesting problem is that, because networks at the edge are so I mean, it’s such a, there’s so hydrogenous, you’re always dealing with edge cases, no pun intended, you know, the low probability cases that for a particular customer actually became a big deal. Now, that may be one of hundreds of 1000s of or customers you have, but it’s still a problem for that customer. Yeah. So as a business, how do you develop the muscle to be able to identify those problems with edge cases? You know, highlight them, and then, you know, constantly keep solving for them. So that you, you know, have less and less edge cases over time. So, you know, how do the different like teams on the engineering product and sports side work together to make that happen? And then you know, that a hot technique problems that you solve, you’d once you surface it, right, but how do you know that that is that kind of problem? How do you diagnose in a complex system, what the exact issue is, and then actually solving organizational issues to solve?

Matt Watson 26:44
have you guys gotten to the stage yet, where you’re, you have, like, a million cameras in the system are like, what? The hundreds, hundreds of 1000s of cameras, like

Sud Bhatija 26:54
it’s a high number, but it’s at a stage where, you know, we’re feeling really good about there’s been a lot of work, and we have a team that’s dedicated just to that. Yeah. How do you make sure the camera feeds show up? Yeah, that’s, that’s, yeah, that’s it. And then so we’ve got to a good place there. We feel happy about we’ve we’ve come a long way. And obviously, you’re, you’re never done with that kind of thing. You know, as a business reliability record product is always the key for us.

Matt Watson 27:24
So how, what is growth look like for you guys in your go to market strategy? I know you’re your head of growth. Right. That’s, that’s your, your forte. So what is your guys’s sales strategy look like? How do you how do you sell your solution,

Sud Bhatija 27:38
though, you know, we we sell to customers across, you know, 17 verticals. And one thing that’s common across all our customers is customers love to try the product. So the trial is actually a very, very big part of our sales process of free trials, because you know that the way technology is bought today is customers want to see it, they want to see it, they want to use it, they want to it folks want to get feedback from the users and say, Hey, this is this doesn’t look good.

Matt Watson 28:04
So you’re doing a free trial, but you’re shipping them hardware to do a free trial, you’re shipping them hardware to do free trials. Exactly right. You don’t see that very often.

Sud Bhatija 28:11
I mean, it’s something that’s quite crucial, I think, because it enables customers to evolve, if you’re giving them something so new that, you know, they wouldn’t conceptualize exists, right, they need to see it to believe it. Or they need to see it to kind of really, you know, even build consensus in their organization sometimes to to have a black sheep execute on a buying process. So now obviously, as a business that creates complexity for us, we have to send those things, we have to send those failures, how are we going to get them back, we have to make sure that once the unit is plugged in, it works, we have to make sure that we have a customer success team would that make sure that the customer is getting value from the product is setup is you know, fully well versed how to use it and they’re kind of integrated into it. So it actually creates a lot of, you know, organizational mechanics that need to be executed on but what that does is it gives customers a really like really good buying experience we’re not going to hypothesize on what could this be six years what it is, and yes, having a having hardware and it does create a higher bar but but that’s something that we’ve seen is absolutely necessary to our process. So most of our customers always try the product first and then we give to them for like a month and then we give them we give to them for a month and then like they they tried out they see the value and then they die.

Matt Watson 29:43
So from the go to market strategy itself though, is it primarily through phone calls like you’re calling like, all of the car washes and stuff is it is it direct phone calls, or do you guys sell through partners or how do you how do you guys what is like the primary like traction generally use?

Sud Bhatija 29:58
So V V V We sell directly to our customers, we do have a partner program that we’re sending about primarily. So far we have sold like Daddy direct channels are really a mix. A lot of search for video online.

Matt Watson 30:13
Okay? So inbound

Sud Bhatija 30:17
from that, right, you want a camera system, you look on Google. Now, some of those are businesses that you want to target. So those are consumers. But there’s still a lot of them there. So we definitely allow that. And then another piece, like two other pieces that are becoming very important to our market strategy perspective is webinars. Again, we’re what’s what we see happening in the world of b2b selling is, customers want to do their research before they talk to sales. Customers don’t want to get into a sales process. And then the, you know, called 10 times a week by salesperson saying, hey, like, are you buying it, they want to do the research and customers especially IT folks want to be really informed. So customers are looking for these low touch ways to learn about the product in a serial way. So one thing that we have found to be very useful, it actually webinars where customers show up and they actually, like, they want to see a demo of the product. They want to chat with other customers in that webinar and ask questions. They want to see what questions other people have. So another thing that we do, which is we think very helpful, as we’ve, you know, pretty developed webinar program where customers show up every week, the webinar, you can ask questions and learn about the product. And then the third is our bond sells, right? Ultimately, a lot of sales sales, sales comes down to calling people on the phone. Okay, getting getting hold of that person. So it’s a bit of a it’s a mix of all these, okay?

Matt Watson 31:47
I just curious, he’s every business is totally different. So what what do you guys see as the future for this? I mean, what worse? What do you guys working on next?

Sud Bhatija 31:59
So, you know, from our perspective, video surveillance was this category of products that existed for a very long time, people use it once in a while it was just used for security. With this unlocking the value of video, we see a couple of things happening. One is businesses are using video for all these different purposes, and we are making that video useful. And secondly, it’s not just a small set of people or an organization who have access to it, but like everybody does. Video is now becoming a tool that businesses are using in their day to day lives. Whether it be the HR person, or the operations person, or the finance person, or the safety person. They’re all using video to make better decisions and to collaborate. So what we see happening is a new category of products getting created that we call Video Intelligence. It’s like business intelligence, except business intelligence is missing a data stream, it’s actually video. So Video Intelligence is is this character product that we are building and the vision is for the next few years? How do we create and dominate that category, or several different verticals? And from up, there are many things that unlock the value of video, right? One is, you know, AI that’s used to index and analyze the video and give insights to customers. There are more things that are things like that are hardware products that both enable the use of video, and are enabled by the use of video. So how can you use video, for example, doesn’t actuate and create things like create outcomes for the customer? If you figure out something about customers operation? Can you actually, you know, shut down or speed up different things? How can you create those like outcomes for these customers? So that’s another lesson that we think about. And then, you know, we think a lot about how video can be used across different applications. So, you know, video as a data source is something that can be used in, you know, many different systems that customers already have, whether it be support, whether it be safety. So how do we help video like pervade through all the customers business systems, and make it like more useful for them? So those are the different vectors that we think about. And all this sort of comes together in this product category called Video Intelligence, and that’s what we’re building.

Matt Watson 34:24
So do you do you have any potential challenges to achieve those goals? Is there anything that that is standing in your way to do some of these things or, you know, big obstacles that you guys have to work through? Or?

Sud Bhatija 34:37
I think the interesting thing about, you know, video is, you have a lot of customers who intuitively get the value of it and are really looking to do it. You know, you have the early adopters. But then you also have the folks who don’t know this exists from a market perspective, one of the biggest challenges, how do you articulate that value and, you know, get it out there, too. It’s

Matt Watson 35:03
an early market.

Sud Bhatija 35:04
It’s an early market, how do you get a lot of customers,

Matt Watson 35:06
which is very hard? Because it’s like people, people don’t buy that thing. Like my, one of my favorite examples would be like, trying to go to the Philippines and sell toilet paper. It’s like, they don’t use toilet paper. Like, that’s, that’s not a normal thing. Right? So it’s not a market. And that’s a very difficult business to be in, right? When you’re up to like, create a market and like, there’s not people aren’t shopping for that thing. Maybe Maybe they even they need it, but they don’t know that they needed it or not used to buying it.

Sud Bhatija 35:33
Right. And, you know, I think the the advantage that we’ve taken, what we figured out with our go to market strategy is people buy a lot of video surveillance, and video cameras, like security cameras anyway. So we use that as sort of the angle to sell to customers, you it’s many billions of dollars being spent, customers are buying these products. So how do we suddenly get out the door with these customers? And then how do we use this value of video concept the next time? And that’s something that is probably the solution. That is that’s the solution that we’ve been working on these days. And and, you know, helping customers be successful once they had the product, and then building out rich case studies from that, and then using that to go to the next set of customers as we create this gallery. So yes, hard problem. And the way we see it is the price at the end of that tunnel is very, very large.

Matt Watson 36:30
So So tell me what what is the like entry level like price point that somebody uses or pays for your guys’s solution? Like, what is the pricing kind of start at

Sud Bhatija 36:39
the pricing? Typically, so we typically charge for the camera. So it depends on how many camera feeds the customer has, typically, a customer would start in any scenario at about a couple of 1000 a year or so maybe, you know, a couple 100 a month. And then it can go up depending on how many candles actually how many cameras they actually have. And your other customers who have eight cameras or locations or customers that have 300 cameras are located that have 2000 cameras.

Matt Watson 37:09
Yeah, so that was my next question for you is like What is the craziest thing you’ve seen, like you have a customer is like a casino or like some crazy thing or,

Sud Bhatija 37:17
or the craziest thing we’ve seen are and we see this with a very, very, like, you know, forward thinking output and customers is. I mean, they have cameras, the number of cameras they have, and they use it for operating purposes and their manufacturing. But they have an order of magnitude more cameras, and they work for security. So the warehouse has like, you know, 200 plus security cameras, they actually have like 2000 cameras for like, non security purpose. Oh, so that’s, and that’s also where we see the word going, we see the word going to a place where the, you know, the camera density is increasing. And that’s driven by these really specific use cases that you have all these industry verticals. So you won’t have that in every vertical, you will have that.

Matt Watson 38:00
So for that kind of warehouse, like what are they trying to do? What are they tracking with all these cameras?

Sud Bhatija 38:05
They’re tracking their manufacturing and distribution lines. So what they want to know is, you know, how is the manufacturing line progressing at like every point, and they’re trying to get ahead of problems. Because if you have problems, you’re not able to, you know, you actually lose money, right? You produce bad widgets, or you know, your wastage or new you can sell them. So the business case is so strong that allows them to have

Matt Watson 38:30
these many gaps. Right. Interesting. And we

Sud Bhatija 38:33
see this more in regulated industries compared to others as well. So you know, regulated industries have a lot of requirements like cannabis around needing a certain number of cameras in every part of your business.

Matt Watson 38:43
Yeah, I can see I can see to be a huge need for this for cannabis related stuff. Because like they have to track if I remember, right, like every plant and all this stuff. Like there’s an enormous amount of tracking that goes on.

Sud Bhatija 38:55
That’s exactly right. So so. So manufacturing about I was definitely on the higher end of the density of campuses.

Matt Watson 39:04
Interesting. All right. Well, if you need to hire software engineers, testers or leaders Full Scale can help we have the platform and the people to help you build and manage a team of experts when you visit full scale.io. All you need to do is answer a few questions and let our platform match you up with our fully vetted, highly experienced team of experts. At Full Scale. We specialize in building long term teams that work only for you learn more when you visit FullScale.io dot io. Well, thank you so much for being on the show today. You know, as we wrap up the show, is there any any final thoughts or words of wisdom for for listeners?

Sud Bhatija 39:42
I can think building a business has been probably one of the most meaningful things I’ve done. And I mean, I know a lot of your audiences is that it’s hard and I think what Things that as founders we don’t talk enough about is our own mental health and our own personal development. And I think that’s something I personally found a whole lot of benefit engaging with. And I know that it’s, it’s something a lot of us struggle with and don’t talk enough about. So I think, as a community, I hope what I hope for us is that we spend more time engaging than talking about that, and that people spend more time you know, focusing on that for themselves, because doing that allows us to build our companies that

Matt Watson 40:34
Well, I think everybody needs a friend, a mentor, advisor, people they can relate to that are entrepreneurs because it’s definitely it’s its own world and most people can’t relate to so I totally agree. It’s correct. Well, everybody This was sued, but Teesha and his company is spot.ai. If you need a really intelligent camera system, definitely check out his company as well. And thank you so much for being on the show today, man.

Sud Bhatija 41:01
Really appreciate it. Man. Had a great time. Thank you. All right.

Matt Watson 41:04
Take care.