Back in the early 2010s, Mukul was hard at work helping Toyota determine how computers could use cameras to interpret and interact with the world. But Mukul had a problem - every day, he would go to get his lunch, and every day he’d spend most of that time (30-40 minutes) waiting in line in his corporate cafeteria. He decided to take a closer look at the issue and decided that computer vision could be the answer. After some initial testing, Mukul felt the idea was a big opportunity and flew to California to pitch his idea.There he reconnected with Abhinai, who was his classmate in the same dorm at IIT Delhi. He created an early demo that was so impressive that it convinced Abhinai to join him.Having worked in large companies and created some enormously successful projects, we were disheartened by the fact that when a project became successful, several people came in at the final stages to take credit. We decided to be founders and create a company that valued people’s contributions honestly and cut through the corporate bullshit.After successfully cold-calling head executives from some of the largest corporate cafeteria operators on the planet, we received many enthusiastic responses to our description of Mashgin’s Touchless Checkout System. He then set out to actually build it.After successfully building and demoing a Mashgin prototype to the YC team, Mashgin went from “project” to “company” over the course of the Winter 15 Batch.
We applied to YC very late, just a few days before the start of W15 batch. We were in the middle of raising a seed round and through our suboptimal interactions with investors, we realized that we needed YC guidance to help us raise a round on good terms. Our YC experience was amazing, if a bit overwhelming at times. YC partners forced us to think clearly about the next steps. At one point they had us go door to door to every business in Mountain View downtown to try and sell our product. We made our first sale that day and we’ll never forget that experience! Fundraising post YC was every bit what we imagined it to be. It made the entire process super smooth and easy.
When we started the company in 2014, our initial goal was to improve the checkout experience in corporate dining facilities, cafeterias, and sports stadiums. We aimed to use computer vision and machine learning technology to create a much more efficient and convenient experience for customers. Entering YC and getting to demo day with a major letter of intent was a big moment for the company, giving us the experience and fundraising to make Mashgin market-ready over the following few years.However, with the outbreak of COVID-19 in 2020 and the subsequent lockdowns, we had to pivot our focus to the convenience store space as corporate offices closed and retail demand for self-checkout solutions skyrocketed.During the pandemic we were able to secure an enormous deal with Circle K, one of the largest convenience store chains in the world, for 10,000 kiosks across their global portfolio of stores. This elevated us from a burgeoning player in AI to the most market-tested solution in the world.In May 2022, we were able to announce a Series B funding round of $62.5 million with a valuation of $1.5 billion, earning us the title of “unicorn” company. The round was led by NEA, a global venture capital firm that’s invested in other successful startups like Cloudflare, Patreon Plaid, and Robinhood, with additional support from our existing investor, Matrix Partners.Today Mashgin continues to expand within the convenience, sports, and corporate dining industries while beginning to explore adjacent opportunities in spaces like ski resorts, quick service restaurants, and drug stores.
Online retail has gone through several iterations in the past few decades and the experience today is extremely frictionless. Physical retail on the other hand has not seen the same level of innovation and the experience hasn’t changed much since the early 90s. We want to use the latest advances in AI and Computer Vision to make physical retail as easy and frictionless as online retail.More specifically, Mashgin solves the problem of long wait times and checkout bottlenecks. Customers often experience frustration and dissatisfaction when they have to wait in long lines to check out, and retailers also face the challenge of managing and staffing checkouts. This is a big problem because lines are a waste of time for everyone involved. Over the course of a lifetime, the average person will spend years waiting in lines. And those lines aren’t just wasted time for consumers, they result in lost sales for retailers. Studies by Forrester and BlueDot have shown that retailers lose as much as 57% of their sales when customers perceive the line as long (which in a convenience store is 3 people).Besides being frustrated by our own lunch lines, we decided to work on this problem because we saw an opportunity to use computer vision and machine learning to create a more efficient and convenient shopping experience for customers across industries.
At Mashgin, our long-term vision is to create a world where the shopping experience is completely seamless and frictionless. If we succeed, waiting in line to purchase goods will be a thing of the past. Consumers will have more time to do the things that they love with a faster, more convenient, and less stressful experience in retail and dining spaces. For retailers and concessionaires the technology will free up time and resources, allowing them to focus staff on other key areas of the business like stocking, cooking, cleaning, and customer service.