AI-enabled security startup MokSa.ai raises $1.5 million in funding

• Nikhil Teja Kolli’s startup MokSa.ai uses AI security cameras to combat theft and fraud.
• Since launching a year ago, MokSa.ai has amassed over 70 customers and $240,000 in ARR.
• MokSa.ai has secured $1.5 million in pre-seed funding and is looking to expand its operations.

When he was a college student in Kansas, Nikhil Teja Kolli worked the night shift at a grocery store on the edge of the Ozarks. One evening, a man lingered in the store until the other customers had left, then approached the counter with a gun in Kolli’s direction. The gunman swiped the money from the drawer, leaving Kolli frozen. He felt helpless to stop it.

Eight months later he would be held at gunpoint again.

He couldn’t have known it at the time, but Kolli would start a company focused on combating theft.

His startup MokSa.ai, which aims to help companies combat theft and employee fraud using artificial intelligence-powered security cameras, launched from stealth less than a year ago. But it already has a large number of paying customers, which is rare for startups of this size. According to Kolli, the real-time monitoring system is used at more than 70 gas stations, liquor stores and bodegas across the country and generates $20,000 per month in recurring revenue.

Now, this powerful cocktail of machine learning and profits has convinced investors to provide the company with pre-seed funding. MokSa.ai tells Business Insider it closed $1.5 million in a March round led by Array Ventures, with participation from Jay Farner, the former CEO of Quicken Loans, and The Fund Midwest.

The company uses computer vision to automate some parts of surveillance that are still done by humans. It makes software for off-the-shelf security cameras that detect suspicious activity (think someone stuffing a six-pack of beer down their pants or a cashier giving away merchandise to a friend) and sends a real-time notification to the customer. dashboard. The alert includes a clip of the incident, saving the business owner time from replaying hours of CCTV footage.

Kolli said the company initially tried using open-source, pre-trained artificial intelligence models, but found that some of these models had biases that were representative of the datasets they were trained on. It then tried to refine those models, but Kolli said their performance fell apart. Ultimately, it came down to using general-purpose models that continuously learn as new images arrive.

The company also pays interns in India to review footage for suspicious activity and annotate it – a process called data labeling.

“As we sit and speak, new data is coming in and these models are getting better and better,” Kolli said.

According to Shruti Gandhi, the founder and sole general partner at Array Ventures, part of the magic of MokSa.ai is the tailor-made models for this use case.

“The datasets they have collected over the past two years as a service company have allowed them to deploy trained models to customers from the first week of onboarding,” she says. “That’s not possible at many business intelligence companies today, because most think they will get better once they have customer data. The reason some companies will win over others in the same category is their access to unique, differentiated data. .”

Since MokSa.ai’s software works with a range of internet-connected security cameras, it positions itself as the Android of the surveillance market. The company will also provide a company with the cameras it needs in exchange for signing a multi-year contract. It charges a monthly subscription that scales based on the number of cameras used.

Customers can pay extra if an operator calls them when the system detects an event, and that’s as far as MokSa.ai’s responsibility extends, Kolli said. No contact is made with the police.

“We offer a surveillance audit platform,” he said. “So it’s up to the customer to understand what they want to do with the information we provide.”

The Android of the surveillance market

Before MokSa.ai, Kolli worked as a quality manager at a company that produced parts for high-speed rail. He became interested in building this business after talking to a friend who owned the gas station and liquor store where he worked in college. The friend had discovered that an employee had stolen thousands of dollars worth of merchandise and cash and asked Kolli how technology could catch bad actors. The idea planted the seed for what would become MokSa.ai.

Later, Kolli enrolled in the startup accelerator Techstars Detroit, where one of his mentors introduced him to his future investor.

Kolli told Gandhi the MokSa.ai story over the phone. He didn’t have a pitch deck to show her, nor did any other investor promise to push her into action. But Array Ventures’ founder bought the round before the call ended. The next day Kolli had a term sheet.

The investment was a no-brainer, Gandhi said.

The company is now preparing for growth. MokSa.ai just signed a contract with Royal Ozarks, a major commercial real estate developer in the South, to deploy its system in 150 retail locations. Kolli said the partnership will bring annual recurring revenue from $240,000 to more than $1 million this year.

The new funding will allow the company to expand its sales and customer support teams as part of this expansion. We are also working on releasing a mobile app that will allow business owners to view their notifications on the go.

In its bid to create a smarter surveillance system, MokSa.ai is facing competition from startups like Verkada, a maker of building security tools that has raised more than $360 million in funding, and Rhombus, a newer entrant that just raised $26 million in capital has announced. While these two tout their abilities to detect suspicious activity and send alerts, they both require customers to use their cameras and sensors.

That could be the wedge that gives MokSa.ai a chance despite being much younger than its competitors.

Gandhi summed it up: “What they’re saying is: keep your camera, we’ll figure out how to best use this camera.”