Tech Behind Kitchen Automation Startup Mukunda Foods
Bengaluru-based Mukunda Foods was founded in 2013 by college students Sudeep Sabat and Eshwar K Vikas as a Quick Service Restaurant (QSR) the same year to sell South-Indian food. While initially, the business was doing fine, challenges popped up when the founders tried scaling up the business and opening more outlets. Like most QSRs operating before the kitchen-automation era, Mukunda Foods couldn’t maintain consistency across its outlets, and that automatically affected its customer base. This was the founders’ first encounter with market reality in the Food and Beverages industry– scaling is tough, but maintaining consistency and controlling operational costs can be tougher. This was when Mukunda Foods pivoted from a QSR to a kitchen automation provider. Its first product, Dosamatic, was launched in 2016 and is a fully automatic dosa-making machine. Today, Mukunda Foods powers clients across the F&B industry–cloud kitchens, fine-dining restaurants, QSRs and hotels. It has automated more than 3000 kitchens across 22 countries, including that of food tech unicorn Rebel Foods, ITC, Ola Foods, Wow! Momo, Good Flipping Burger, Biggies Burger, Carnival, Samosa Party, and more. In a conversation with Analytics India Magazine, Rakesh Patil– Co-founder and CTO of Mukunda Foods, takes us behind the scenes of a kitchen automation business, diving deep to understand how artificial intelligence (AI) and machine learning (ML) come into play in smart kitchens and can help QSRs maintain consistency across outlets. “Maintaining food consistency is challenging for reasons like high attrition rate and SOPs not being followed. Automation could successfully bridge this gap where machines cook chef’s recipes with zero SOP deviation. This ensures the same taste across all the outlets, and the dependency on skilled staff also goes down. Getting automation also brings operational efficiency to businesses and also helps brands to sell faster,” Rakesh said. An MTech degree holder in Product Design and Manufacturing, Rakesh has earlier worked with Hindustan Aeronautics Ltd., where he developed engines for TEJAS Aircraft. Rakesh joined the Mukunda Foods team in 2015 and is responsible for developing the tech products from scratch and identifying new technologies for the future-ready commercial kitchen. Additionally, he also oversees the company’s research and development team and participates in strategy, standards, specification and processes planning. Edited excerpts from the conversation: AIM: How large is the tech team? Rakesh Patil: I have around 35 people in my team, including the design team, embedded electronic team, Android and IOT team and the COE team (new product development, image process, AI/ML, prototyping, etc.). AIM: Name a few kitchen automation products developed by you and your team and explain the work. Rakesh Patil: So far, we have automated around 14-plus processes, and most of these solutions are cuisine-specific and problem-solving in nature. Besides our flagship product Dosamatic, we have Wokie, the automatic wok used for Chinese food, Indian and Thai gravies; Rico is the automatic rice, noodle and pasta-maker; and Eco-fryer is used for frying french fries, momos, samosas, and burger patties in less oil. Our latest addition, an E-pan, is designed to counter challenges faced by food businesses concerning blackening. It helps regenerate frozen, par-baked, fresh food items like flatbreads, kebabs and patties in their fresh and original taste. Kitchen automation machines by Mukunda Foods | Source: Mukunda Foods AIM: How are you leveraging AI/ML at Mukunda Foods? Rakesh Patil: We are making machines smart by using AI and MI technology, which help our clients save time, money, and manpower and deliver consistent food to their customers. For instance, we have been using AI/ML with image processing in Wokie to make multiple cuisines from the same machine. The machine captures an image of each ingredient, also weighs and maps with the pre-loaded recipe and makes sure the operator doesn’t deviate SOP and also alerts the operator in case of deviation. The machine is also connected to POS and reads the instructions provided by the customer (less oil or spicier), and automatically customises the standard recipe. Wokie by Mukunda Foods | Image Source: Mukunda Foods AIM: What tech tools do you use? Rakesh Patil: We have been using TensorFlow, Pytorch, AWS(IoT), Firebase, and Postman in the backend for our AI/Ml and Image Processing. In the frontend, we have developed multiple Android applications which help customers create their recipes, remotely monitor machines, and request services using the same application. Also, we have been using HTML5 for web page development to display all the analytics to the customer at a different level and plan the operation and stock at each store accordingly. AIM: Explain how you leverage AI and ML in your client’s kitchen. Rakesh Patil: One of our clients, Wow! Momo, was facing concerns regarding the under and over-frying of the items. They were looking for a solution to solve this problem and save operational costs. Mukunda Foods worked on the project for almost a year and came up with the automatic Eco-Fryer. The fryer enables the operator to select the recipe to be cooked; once the food is put in the basket, the fryer automatically maintains the pre-set oil-frying temperature, and the basket automatically gets dipped. So, the food gets cooked at a set temperature and time. Also, features like double-dip, sleep mode, and deep-sleep mode helps save electricity and oil cost by 25 to 30 per cent. In addition to this, the AI helps us understand order trends, peak hours, etc. This also helped in maintaining the temperature of the oil, leading to less wastage and expenses. We are further working on integrating image processing to Eco-Fryer, which will help auto-select the recipes. AIM: Do you think kitchen automation is just a trend or is it here to stay? Rakesh Patil: Automation is surely here to stay and gradually be a part of every commercial kitchen. It might have taken some time for the Indian market to acknowledge it, but the pandemic gave the industry enough reasons and time to evaluate it. Moreover, the shortage of skilled staff and labour due to the migration, and with hygiene and safety becoming a priority in the post-pandemic world, automation adaptation increased. This got validated when not just large food chains but small businesses owners also started automating their kitchens. AIM: How can traditional food companies adopt technology? Rakesh Patil: Embracing the change and adopting technology with time is a must for all kinds of F&B businesses. Pandemic just accelerated this evolution, and traditional food companies are no exception. The industry witnessed technological advancements at different levels of the business ecosystem– supply chain and logistics segment, packaging of the food, and digitisation of the menu cards. Talking specifically about us, traditional food companies have always been a major contributor to our business. For example, stand-alone outlets and small chains form about 50 per cent of our revenue. AIM: What are Mukunda Foods’ future plans? Rakesh Patil: While we have installed machines across 22 countries, we have never taken consistent efforts to penetrate into the international market. Our immediate plan is to aggressively expand to the UK and US markets. We have recently ventured into KAAS (Kitchen-as-a-Service), enabling brands to expand their cloud kitchens to a new location with a fully automated operational kitchen with CaPex and OPex-lite models. Our first kitchen became functional around two months back, and the response has been great, so the plan is to look at the expansion of KAAS. AIM: Does the Indian ecosystem have enough opportunities available for food tech startups? How is the Indian food tech market different from its western counterparts? Rakesh Patil: COVID-19 did hamper the growth of food businesses, but things are gradually getting back to normal. We can already see a lot of F&B players raising investments and scaling, which imposes a big demand for food-tech startups. The Indian food-tech market is significantly different from western counterparts, especially when it comes to kitchen automation. The solutions come with robotic arms and a lot of aesthetic value; however, we build more functional machines. The Indian market may not prefer higher-priced machines that can’t ensure return-on-investment (ROI). A food business can expect ROI in a maximum of six months with any of our automation.
Mukunda Foods has automated 3000 kitchens across 22+ countries, including ITC, Rebel Foods, Wow Momos and Ola Foods.
Mukunda Foods has automated 3000 kitchens across 22+ countries, including ITC, Rebel Foods, Wow Momos and Ola Foods.
["food tech", "Machine Learning"]
["artificial intelligence", "machine learning", "AWS", "AI", "PyTorch", "food tech", "ML", "Machine Learning", "RAG", "Aim", "analytics", "TensorFlow"]
["AI", "artificial intelligence", "machine learning", "ML", "analytics", "Aim", "TensorFlow", "PyTorch", "RAG", "AWS"]
After diving deep into the Indian startup ecosystem, Debolina is now a Technology Journalist. When not writing, she is found reading or playing with paint brushes and palette knives. She can be reached at debolina.biswas@analyticsindiamag.com