CCTV and other types of security cameras have a strong Big Brother vibe to them, but for many of us that may be because we don’t really understand or know how the images they capture are used. Now a startup called Spot AI has built a system to help answer that question at least in part – it provides a cloud-based analysis system that “reads” those images to get insights into not just security, but also on security and operational activity – announces funding of 40 million dollars to develop.
Scale Venture Partners is leading the round, with former backers Redpoint Ventures, Bessemer Venture Partners and new investors StepStone Group and Modern Venture Partners also investing. This brings the total raised by Spot AI to $63 million. Spot AI, as it should be for a security camera company, existed in stealth for years before going public in 2021: by then, he had already raised $22 million.
As with this round, Spot AI is not disclosing its valuation, but Spot AI CEO Tanuj Thapliyal noted that this is a “significant upside round” based on the fact that over the past 12 In recent months, the startup’s revenue has increased fivefold, and that customers – it has “thousands” in the United States, both small businesses and large corporations in some 17 industries, which aren’t really the ones that include “knowledge workers” per se, but companies in areas like manufacturing and retail that have critical physical components and a lot of activity – have tripled over the same period. Its customers include SpaceX, transportation company Cheeseman, Mixt and Northland Cold Storage.
And it turns out that giving people a better reason to use their video cameras makes them much more interested in using and watching that video data.
“People use our cameras a lot,” Thapliyal said in an interview. “Forty percent of our monthly active users log in every day. There is value to be had here.
Fundraising has gotten really tough recently, but Thapliyal said the San Francisco startup hasn’t seen it for itself, partly because of those growth numbers and also because it’s bringing something different. on the market.
CCTV and other security cameras have become as ubiquitous as electric lighting in many workplaces these days, especially those with high traffic. Spot AI estimates that since 2015, the number has doubled and now stands at 1 billion devices worldwide. In many cases, the cameras are networked and linked to larger systems where the footage can be viewed by security teams. But that’s usually where a lot of the usage ends, and so that’s where Spot AI hopes to pick things up.
Spot AI provides different levels of service: for customers who already have network cameras, they can integrate them into the Spot AI platform so that it can start reading and analyzing video data. Those who don’t already use cameras or have networked systems, or want the full system as envisioned by Spot AI, can potentially use free hardware built and provided by Spot AI itself.
This system is based on technology that uses computer vision and other AIs both in the cloud and at the edge (for example, if you’re using Spot’s own cameras) to monitor video through the settings of safety, but also others around safety, efficiency and movement in general. What is monitored, and where, is configured by customers themselves through a drag-and-drop interface that allows them to select specific items or areas within a frame, which the system can then scan over a range of specified time for shifts and other types of activity.
One scenario Thapliyal described was how a car wash used its system to help resolve damage claims by locating video to identify when and was, and if, damage was done during a car wash to help those claims to advance. Another solution you might imagine would be to help a store determine where and where customer assistants spend time, and if they might be better positioned at different times of the day.
Longer term, there are exciting opportunities for Spot AI’s platform that it is not yet pursuing, particularly in the consumer segment. Thapliyal said direct-to-consumer selling — for example, relying on the marketplace Ring has created so cameras can track who comes to people’s doorsteps — isn’t one he wants to pursue, but he just might. there is an opportunity to work with companies who, in turn, work with consumers.
Thapliyal – who co-founded the company with Rish Gupta and Sud Bhatija – thinks that with all of this, the opportunity to make this video useful is the way to make video less scary and even less inactive.
“If you create the video data [produced by these cameras] more useful and accessible to more people in the workplace, so you move from this idea of surveillance to the idea of video intelligence,” Thapliyal told me in 2021. “It can help you take all kinds of important decisions. As I said before, its philosophy seems to stem from the idea that these cameras are out there, so we need to find better ways to use them more efficiently and responsibly.
It has definitely lifted the business today and helps shape future strategy.
“For a company like ours to have an impact, we have to be very specific in our focus,” Thapliyal told me this week.
An interesting scenario where Spot AI could have a place, for example, is in the realm of connected cars, where automakers might want to tap into the trend of dashcams that drivers use to help them file accident claims. Many cars already have cameras built into their vehicles, but no additional ability to analyze or use this video data beyond the immediate purpose, for example, helping people park.
“The product usage and engagement Spot AI has seen with their customers in the year since launch is a testament to the unique software they’ve built and the speed of their product engine,” said Jeremy Kaufmann, partner at Scale Venture Partners, in a report. “There is a huge opportunity here and we are excited to partner with Spot AI as they continue to unlock the value of video data.”