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Dishq Uses Machine Learning for Bespoke Food Recommendations

by Chris Albrecht
January 31, 2018February 2, 2018Filed under:
  • Restaurant Tech
  • Robotics, AI & Data
  • Startups
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This is embarrassing to admit, but whenever I go to a Thai restaurant, I just order tofu phad thai. Always. Yes, that is totally generic, but I don’t get to eat out that often, so I don’t want to take a chance on something that I might really dislike. I know what I’m getting with the phad thai, so I settle.

It’s that settling for the same-ole that Dishq is looking to improve by using artificial intelligence. Based in Bangalore, India, Dishq provides APIs for food service companies like restaurants, corporate cafeterias or food delivery services, so those companies can implement AI-powered, customized food suggestions for their customers.

During an interview, Dishq Co-Founder and CEO Kishan Vasani told me there are four parts of his company’s offering:

  • A database of more than 100,000 dishes that are broken down into 26 different attributes including ingredients, cuisine style and cuisine origin
  • Anonymized customer behavior analytics data
  • A machine learning algorithm
  • Food science research from around the world that feeds into Dishq’s algorithm

Vasani said that the collaborative filtering used by Amazon or Netflix to make suggestions won’t work for food because meals are such a personal experience. “Too many things go into it,” said Vasani, “What you like, where you grew up, who you’re with.” He says that Dishq’s deep data-driven approach allows for truly bespoke recommendations because it understands food at the flavor compound level as well as transaction history.

Where the customer encounters those recommendations are up to the company using Dishq’s API. It can be used at the menu level to surface suggestions or email notifications. It depends on whether that client is looking for more conversions, increased average order value, or just creating a better customer experience.

Right now Vasani says that Dishq has 6 clients with two million recommendations generated every month, and that clients see an 11 percent uplift in revenue with Dishq.

Sadly, Dishq can’t offer a universal taste passport that travels from restaurant to restaurant. So what you like at Domino’s would help them determine what you might like at Dunkin’ Donuts. The reason for that, Vasani says is data protection and restaurants not wanting to play nice with one another.

Founded in 2015, Dishq has 13 employees and has raised $160,000 to date, with $120,000 of that coming from the Hong Kong-based AI accelerator Zeroth.ai. Vasani says he plans to start looking for new funds in Q2 of this year.

Vasani is also looking to expand beyond food service clientele and into the consumer packaged goods. He refers to the forthcoming product as “Taste analytics as a service,” and would allow CPG companies to react more quickly to food trends as they are happening. For example, if avocados were suddenly appearing everywhere on Instagram and social media mentions around Nashville, Dishq’s data could help a CPG company spot and understand those trends to quickly ramp up some avocado-related product for that location.

Until then, however, Dishq just wants to make eating out more pleasurable. Vasani wants Dishq’s recommendations to “shift people’s experience from a 6 out of 10 to an 8 or 9,” said Vasani. If Dishq works as promised, that could mean a lot less phad thai for me in the future.


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Tagged:
  • AI
  • artificial intelligence
  • Dishq
  • machine learning

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