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 footage they capture is being used. Today, a startup called Spot AI has built a system to help answer at least part of that question—it’s providing a cloud-based analytics system that “reads” that footage to gain insight into not only security, but also for safety and operations – announces $40 million in growth funding.
Scale Venture Partners is leading the round, with previous 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, fit for a security camera company, existed in stealth for years before going public in 2021: at this point it has already raised $22 million.
As with this round, Spot AI did not disclose its valuation, but Tanuj Tapliyal, CEO of Spot AI, noted that it was a “significant improvement” based on the fact that over the past 12 months, the startup’s revenue has grown fivefold , and that the customers – there are “thousands” in the US, both small businesses and large enterprises in about 17 industries, which are not actually those that include “knowledge workers” per se, but businesses in areas such as manufacturing and retail, which have critical physical components and a lot of activity—have tripled over the same period. Among its clients are SpaceX, the 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 viewing 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 here.”
Fundraising has become very challenging recently, but Thapliyal said the San Francisco startup hasn’t seen that in part because of those growth numbers, but also because it’s bringing something different to 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, cameras are networked and linked into larger systems where footage can be viewed by security teams. But that’s usually where much of the usage ends up, and that’s where Spot AI hopes to take things.
Spot AI provides several different levels of service: for customers who already have network cameras, they can integrate them with the Spot AI platform so that it can start reading and analyzing the video data. Those who no longer use cameras or network systems, or want the full system envisioned by Spot AI, can potentially use free hardware created and provided by Spot AI itself.
This system is based on technology that uses computer vision and other AI both in the cloud and at the edge (eg if Spot’s own cameras are used) to monitor video through security parameters, but also others around safety and efficiency and movement in general. What is monitored and where is set by the customers themselves through a drag-and-drop interface that allows them to select specific elements or areas within a frame, which the system can then analyze over time for changes and other types of activity.
One scenario Thapliyal describes is how a car wash uses its system to help resolve damage claims by pinpointing video to identify when and if, and if, damage has occurred during a car wash to help those claims to continue. Another you can imagine might involve helping a store determine where customer assistants are spending their time and where and if they can be better positioned at different times of the day.
In the longer term, there are some interesting opportunities for Spot AI’s platform that it has yet to pursue, particularly in the consumer segment. Thapliyal said that selling directly to consumers — for example, building on the market created by the likes of Ring for cameras to track who comes to people’s front doors — is not something he wants to pursue, but that there may be an opportunity to work with businesses , which in turn work with users.
Thapliyal – who co-founded the company with Rish Gupta and Sud Bhatija – believes that with all of this, making this video actually useful is the way to make it less creepy and really less empty.
“If you’re doing the video data [produced by these cameras] more useful and accessible to more people in the workplace, then you transform it from this idea of surveillance to the idea of video intelligence,” Thapliyal told me in 2021. “It can help you make all kinds of important decisions.” As I said before , its ethos seems to stem from the idea that these cameras are here, so we need to find better ways to use them more efficiently and responsibly.
This has definitely elevated the company today and helps shape future strategy.
“For a company like ours to have an impact, we have to be really specific about our purpose,” Thapliyal told me this week.
One interesting scenario where Spot AI could have a place, for example, is in the field of connected cars, where automakers may want to tap into the trend for dash cams that drivers use to help them potentially claims in the event of accidents: Many cars already have cameras built into their vehicles, but have no additional capability to analyze or use that video data beyond the immediate purpose of, say, helping people park.
“The product usage and engagement Spot AI has seen with their customers in the past year since launch is a testament to the unique software they’ve built and the speed of their product engine,” said Jeremy Kaufman, partner at Scale Venture Partners. in a statement. “There’s a huge opportunity here, and we’re excited to partner with Spot AI as they continue to unlock the value of video data.”