Food Industry Innovators Discuss Deep Tech as a Competitive Advantage

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Food Industry Innovators Discuss Deep Tech as a Competitive Advantage

Deep Tech is a new chapter in the innovation story, bringing together science, engineering and design-thinking to open up a wave of opportunities in the food industry. At Ai Palette, we are using it to sharpen and accelerate flavour and ingredient innovation. What used to require years-long research now happens in months using a Deep Tech approach.

What else can Deep Tech offer the food industry? And how can companies tap into the Deep Tech approach to innovation, to benefit your business?

These questions are discussed in The Deep Tech Difference, a panel hosted by SG Innovate and Hello Tomorrow Asia in partnership with OVHcloud, featuring:

  • Massimo Portincaso, Chairman, Hello Tomorrow
  • Roy Tharakan, Regional Director – Commercial Excellence, Cargill
  • Somsubhra Gan Choudhuri, Co-Founder & CEO, AI Palette
  • Arun Narayanaswamy, Co-founder and Head of Products,

Our key takeaways:

On how a Deep Tech approach helps digital transformation in the food industry

“Digitizing and modernising helps us to identify ways in which we can drive efficiency and lower cost down internally. Adopting AI and technological tools has led to diverse solutions that have helped us improve customer experience. With the help of the Deep Tech approach possibilities are unlimited. We are also helping businesses out there not directly relevant to Cargill, like supporting farmers in terms of giving them the support they need with data analytics and technology to improve their livelihood.”

On ensuring a successful collaboration between corporates and startups

 Start-ups have helped us to quickly define our problems. Ai Palette has helped us by looking at consumer insights. Traditional methods would take up to 2 years but AI has shortened this process using predictive analysis. Ai Palette uses data points in social media data and real-time data and incorporates that in our solution. This has helped us to look at future trends and has reduced the failure rate in new product innovations

Cargill was open and ready to invest their resources to use AI in order to understand their consumers better. They also provided the right feedback to help us align our models and algorithms so that we could meet their needs.

On using automated learning and continuous iteration to accelerate problem-solving

 We help companies with new product innovation by identifying what consumers are going to want next. For some tasks, we rely on continuous feedback loops to improve our AI models without manual review or training models. For example, our forecasting models automatically trigger training whenever required, based on the threshold value in terms of the accuracy that falls beyond a certain limit.

The other piece is bringing the human into the loop. We make sure there’s supervised learning, because when it comes to a domain like food and beverage, domain understanding is crucial for developing platform features that are relevant to our customers.

On the readiness of the food tech industry to adopt Deep Tech approaches

The industries that are leading so far are the Food and Cosmetics industries. Food is where you will see a big shift in the next months. In the longer term, the biggest potential is going to be on the agriculture and the materials side, but it will require a lot of time to get there.