Bengaluru-based Mukunda Foods was founded in 2013 by students Sudeep Sabat and Eshwar K Vikas as a Quick Service Restaurant (QSR) in the same year to sell South Indian food. While the business initially did well, challenges arose as the founders tried to expand the business and open more outlets. Like most QSRs operating before the era of kitchen automation, Mukunda Foods was unable to maintain consistency between its outlets, which automatically affected its customer base.
This was the founders’ first encounter with market reality in the food and beverage industry – scaling is difficult, but maintaining consistency and controlling operating costs can be more difficult. That was when Mukunda Foods moved from a QSR to a kitchen automation supplier. Its first product, Dosamatic, was launched in 2016 and is a fully automatic dosa making machine.
Today, Mukunda Foods powers its customers across the entire F&B industry: cloud kitchens, gourmet restaurants, QSRs and hotels. It has automated over 3,000 kitchens in 22 countries, including 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 from Mukunda Foods, takes us behind the scenes of a kitchen automation company, diving deep to understand how artificial intelligence (AI) and machine learning (ML) come into play in smart kitchens and can help QSR to maintain consistency between points of sale.
âMaintaining food consistency is difficult for reasons such as high attrition rate and non-compliance with SOPs. Automation could successfully bridge this gap where machines prepare chef’s recipes without any SOP gaps. This ensures the same taste in all points of sale and the dependence on qualified personnel also decreases. Automation also brings operational efficiency to businesses and also helps brands sell faster, âsaid Rakesh.
With an MTech degree in product design and manufacturing, Rakesh previously 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 technology products from scratch and identifying new technologies for the future-ready commercial kitchen. In addition, he also oversees the company’s research and development team and participates in the planning of strategy, standards, specifications and processes.
Edited excerpts from the conversation:
OBJECTIVE: How big is the technical team?
Rakesh Patil: I have about 35 people in my team, including the design team, the on-board electronics team, the Android and IOT team, and the COE team (new product development, image processing, AI / ML, prototyping, etc.).
OBJECTIVE: Name a few kitchen automation products developed by you and your team and explain the work.
Rakesh Patil: So far we’ve automated about 14+ processes, and most of those solutions are kitchen specific and problem-solving. Besides our flagship product Dosamatic, we have Wokie, the automatic wok used for Chinese cuisine, Indian and Thai sauces; Rico is the automatic manufacturer of rice, noodles and pasta; and Eco-fryer is used to fry French fries, momos, samosas and hamburger patties in less oil.
Our latest addition, an E-pan, is designed to counter the challenges faced by food companies regarding darkening. It helps regenerate frozen, precooked and fresh foods like flatbreads, kebabs and patties to their fresh and original taste.
Kitchen automation machines from Mukunda Foods | Source: Mukunda Foods
AIM: How are you leveraging AI / ML at Mukunda Foods?
Rakesh Patil: We make machines smart using AI and MI technology, which helps our customers save time, money and manpower and deliver consistent food to their customers.
For example, we used AI / ML with image processing in Wokie to prepare multiple cuisines from the same machine. The machine captures an image of each ingredient, weighs and also maps with the preloaded recipe and makes sure the operator does not deviate from the SOP and also alerts the operator to any deviation. The machine is also connected to the point of sale and reads the instructions provided by the customer (less oil or more spicy), and automatically personalizes the standard recipe.
Wokie by Mukunda Foods | Image Source: Mukunda Foods
OBJECTIVE: What technological tools do you use?
Rakesh Patil: We used TensorFlow, Pytorch, AWS (IoT), Firebase and Postman in the backend for our AI / ML and image processing.
On the front end, we have developed several Android apps that help customers create their recipes, remotely monitor machines and request services using the same app. Additionally, we used HTML5 for web page development to show all analytics to the customer on a different level and plan each store’s operation and stock accordingly.
OBJECTIVE: Explain how you are leveraging AI and ML in your client’s kitchen.
Rakesh Patil: One of our clients, Wow! Momo, was facing concerns about under-frying and over-frying items. They were looking for a solution to solve this problem and reduce operating costs.
Mukunda Foods worked on the project for almost a year and developed the Automatic Eco-Fryer. The fryer allows the operator to select the recipe to cook; Once the food is placed in the basket, the fryer automatically maintains the preset oil frying temperature and the basket is automatically immersed. Thus, the food is cooked at a defined temperature and time. In addition, features such as double dip mode, sleep mode, and hibernation mode save 25 to 30 percent on electricity and oil costs.
On top of that, AI helps us understand order trends, peak times, etc. It also helped maintain the temperature of the oil, resulting in less waste and expense. We are also working on integrating image processing into Eco-Fryer, which will help to automatically select recipes.
GOAL: 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 become a part of every commercial kitchen. The Indian market may have taken a while to recognize this, but the pandemic has given the industry enough reason and time to assess it. In addition, with the shortage of qualified personnel and manpower due to migration, and health and safety becoming a priority in the post-pandemic world, the adaptation to automation has increased. This was validated when not only large food chains but also small business owners started to automate their kitchens as well.
OBJECTIVE: How can traditional food businesses adopt technology?
Rakesh Patil: Accepting change and embracing technology over time is a must for all kinds of F&B businesses. The pandemic has only accelerated this development, and traditional food businesses are no exception. The industry has witnessed technological advancements at different levels of the business ecosystem – supply chain and logistics segment, food packaging, and digitization of menu cards.
Speaking specifically of us, traditional food businesses have always been a major contributor to our business. For example, stand-alone outlets and small chains account for about 50% of our revenue.
AIM: What are Mukunda Foods’ future projects?
Rakesh Patil: Although we have installed machines in 22 countries, we have never made a constant effort to enter the international market. Our immediate plan is to aggressively expand the UK and US markets.
We recently ventured into KAAS (Kitchen-as-a-Service), allowing brands to expand their cloud kitchens to a new location with a fully automated operational kitchen with the CaPex and OPex-lite models. Our first kitchen went live about two months ago, and the response has been excellent, so the plan is to look at expanding KAAS.
GOAL: Does the Indian ecosystem have enough opportunities for food tech startups? How is the Indian food technology market different from its Western counterparts?
Rakesh Patil: COVID-19 has hampered the growth of food companies, but things are gradually returning to normal. We can already see many F&B players increasing their investments and growing, which imposes a high demand for food technology startups.
The Indian food technology market is very different from its Western counterparts, especially when it comes to kitchen automation. The solutions come with robotic arms and a lot of aesthetic value; however, we are building more functional machines. The Indian market may not prefer more expensive machines which cannot ensure return on investment (ROI). A food business can expect a return on their investment in up to six months with one of our automations.
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