Food technology group dishq aims to better understand the dietary preference of people, as well as predict their food choices with the use of AI. They are combining food science and machine learning to better understand the relationship between the two. According to CEO Kishan Vasani, they see a massive opportunity in the online food sector helping personalize an individual’s needs. This is a novel way of using better and smarter artificial intelligence in food industry.
AI in Food Industry
The group is steadily increasing their customer base as well as the companies that believe in their vision and goal. However, he also believes that there is a greater opportunity past this. dishq’s AI platform will steadily improve, which will also ameliorate the new solutions that develop along with it. With this steady improvement, it can help revolutionize the way consumer packaged goods (CPG) innovate as well. The group’s long-term goal is to change the huge fast-moving consumer goods (FMCG) landscape by equipping users with personalized recommendations. The goal is to achieve this in multiple platforms and restaurants.
The idea behind a recommendation engine is thatfood preferences are unique to the individual. Working from a baseline, like a questionnaire — and then using actual purchases afterward– the recommendation engine can determine what the person will likely crave for.
Defining a person’s taste in food is not a static project. If it was, the recommendations would slowly spiral towards a small group of favorite foods.
Letting Clients’ Preferences Work for Them
Food preferences are dynamic and involve multiple factors, none of which is the same for every individual. With AI, there is no need to learn what the factors are. The machine learning facility will find out on its own what the individual will most likely order. AI is a freewheeling search and analysis of growing data. A programmed recommendation from known factors would result in an echo chamber, where the food recommendations would always be the same.
Machine learning depends on mining big data, allowing the machine to sift through data and analyze it on their own. This often leads to original insights. With dishq, AI is used starting from the user’s food preferences to the “recommendation engine.” In the restaurant sector, the engine creates custom recommendations to individual diners based on their taste, preferences, and items on the menu. Initially, the engine will be used in online apps. The target market – includes food technology companies and restaurants.
AI and Taste Analytics
After the recommendations engine, dishq’s biggest and most ambitious project is their taste analytics program. They hope to release their very first FMCG- or CPG-based product late this year. The goal is to help various brands develop and build products that match the consumer’s tastes.
With this program, dishq will help several FMCG companies by providing important taste analytics with massive sample amounts.
One of the biggest benefits of AI technology is that it can give companies relevant information from big data that they cannot get elsewhere. This is important because AI can provide more data on certain aspects of sensory testing when done on a massive scale. The plan is to launch the beta test for the taste analytics products in six months’ time. After that, it will take around three more months before dishq can officially launch it as a live platform.
