Virendra ‘Veer’ Mishra, Saurabh Shandilya, Saurabh Yadav, and Viven Singh used to work on different startup ideas at the same coworking space in Delhi. They soon got acquainted and realised they had common interests in deep tech, AI, and ML.
In 2017, the four went for a trip to Udaipur and ended up having a long discussion about deep tech and physics. They realised that while online businesses had something like Google Analytics for data and insights, offline businesses didn’t have anything similar. This discussion led them to start Veda Labs in Gurugram in December 2017.
“Veda Labs primarily is an analytics platform for retailers. Consider it like Google Analytics, but for offline real estate,” Veer says.
What does it do?
Veda Labs uses existing CCTV infrastructure to perform video analytics that present business insights like total footfall, demographic overview, customer journey, and heat maps. It also provides the capability to end customers for tagging and identifying blacklisted people on the premises.
“We deploy an Edge device that gets connected to existing surveillance infrastructure and starts creating an analytics pipeline to process all video feeds for business insights. By analysing entrance cameras, we provide details of how many people entered the premises along with peak traffic on a timestamp and average time spent by each customer in the store,” Veer says.
Veda Labs also provides post-analysis footfall, depending on the body type of each walk-in customer and their facial parameters. It classifies each visitor on the basis of their gender and age group.
Based on each customer’s journey, the video analytics startup anonymously tracks each person and plots a customer journey map and heat maps of the floor. It uses computer vision and machine learning to perform all analytics on the edge and sends all alerts on the dashboard.
The challenges
The team had initial trouble explaining how video analytics in an offline world would work. People usually understand how things work online as each action and activity is trackable. But offline retail has a huge gap in data and understanding.
“This has been the key challenge for us, to educate the customers about how it can work. We simply offered each of our customers a free demo, allowing them to taste the benefits of offline insights, which created a defined understanding and let them know the benefits,” Veer says.
Market and the competition
According to reports, the machine vision market size was valued at $9.6 billion for 2020, and is projected to reach $13.0 billion by 2025; it is expected to grow at a CAGR of 6.1 percent during the forecast period.
Startups like Diycam use video analytics of CCTV footage using robotic process automation (RPA) to help businesses across industries enhance efficiency and reduce dependency on manpower. There also is New York-based Collective Intel, founded by Amit Dhand and Aaron Rhodes, which uses AI to crunch petabytes of video data for retailers to scale up and steamroll their processes.
The team says Veda Labs works with any kind of CCTV camera to extract business insights at the highest accuracies. As a SaaS company, they have a fixed revenue model with a one-time setup/installation fee – that can be let go off if the contract is more than three years – and a fixed per store, per month kind of revenue model. The team refused to share the charges.
Veda Labs claims to have worked with companies like PepsiCo, Panasonic, BMW Automobile, CMR, etc. It has raised $600,000 in seed funding led by undisclosed investors, and is now focused on building “different and newer products”.
