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Daily news and analysis about the food tech revolution

Dishq

Dishq Rebrands as Spoonshot, Acquires Brisky

Personalized food recommendation engine Dishq announced today that it has rebranded as Spoonshot, and that the company has acquired India-based startup, Brisky.

During a phone interview, Spoonshot CEO Kishan Vasani told The Spoon that there were a couple of reasons for the re-branding. First, everyone outside of India pronounced the company’s name wrong (present company included). Evidently you weren’t supposed to pronounce the “q” in Dishq — it was supposed to be said “dishk.”

On a more serious note, the new moniker is also a clever, food-base play on “moonshot,” the big, bold initiatives ambitious companies undertake. Vasani said the name better reflects his startup’s mission. “We’re not a one product company,” Vasani said.

To that end, Spoonshot announced today that it has acquired fellow India-based startup Brisky (terms of the deal were not disclosed). Brisky provides restaurants with a way to gather feedback from consumers in a private, real-time way. Participating restaurants can ask customers to opt-in to use Brisky. If customers do, they receive a text message with a link to a mobile browser where they can rate their experience at that restaurant directly to the establishment, rather than just blasting it out on social media.

Brisky also allows restaurants to check in on customers via SMS mid-meal to see how things are going. This may seem strange for U.S. restaurant goers, but Vasani said that handing over a phone number to a restaurant is more common in India.

The Brisky team will continue to operate independently and will scale that product (it’s in 100 locations in India), but it will also provide another data pipeline to feed Spoonshot’s algorithms. As we’ve written before, Spoonshot is a B2B service that combines behavioral and food science data into its machine learning platform to predict what food you will like. Spoonshot’s service can be embedded into places like self-serve restaurant kiosks or even food delivery apps. Getting direct personal customer sentiment about meals via Brisky will help enhance Spoonshot’s recommendations. Spoonshot will be piloting Brisky up in Canada next before it makes its way down to the U.S.

Based in Bengaluru, India, Dishq Spoonshot has raised $560,000 in venture funding and has just completed it’s run at TechStars Farm to Fork accelerator.

Dishq Raises $400,000 Pre-Seed From Techstars and Arts Alliance

Dishq, the Bengaluru, India-based startup that uses artificial intelligence (AI) to deliver personalized food recommendations, announced today that it has raised a $400,000 “pre-seed” round of financing from several investors including the Techstars Farm to Fork accelerator and Arts Alliance. This brings the total amount of money raised by the company to $560,000.

Dishq combines a vast database of dishes and their attributes, as well as anonymized customer behavior analytics and food science research into a machine learning algorithm. The company’s AI platform plugs into any digital food business, such as Uber Eats or at an in-restaurant ordering kiosk, to provide recommendations for the end-user.

According to Vasani, dishq has 11 customers across 6 countries spanning across more than one thousand restaurants and foodservice locations. The software is powering 30 million recommendations per month with more than 176,000 consumers receiving recommendations each month. For comparison, when I spoke with the company in January, it has 6 customers and was powering just two million recommendation a month.

In addition to TechStars and Arts Alliance, existing investors Zeroth and Artesian Venture Partners also participated in this round, as well as The Syndicate Fund and angel investor Sven Hensen. Dishq says it’s going to use the new money to build out its engineering team and expand sales and marketing activities. In addition to the Bangaluru office, dishq will be growing its presence in London and just opened up an office in St. Paul, MN, which is where the TechStars accelerator is located.

Now is a good time for dishq to bolster its coffers, as the AI-powered recommendation space is getting hot. Just yesterday, Halla announced its I/O platform for B2B food recommendations, and others such as FoodPairing and Plantjammer are all bringing their machine learning to help predict what people want to eat.

This money will also presumably help dishq get closer to its long-term goal of creating a real-time “taste analytics as a service,” which will help CPG brands better react to food trends as they are happening and take action.

Vasani spoke at our recent Smart Kitchen Summit: Europe, where he was on the panel Personalized, Shoppable and Guided: Recipes Are Not Dead. You can watch it here.

SKS Europe: Personalized, Shoppable and Guided: Recipes Are Not Dead from The Spoon on Vimeo.

Dishq CEO Kishan Vasani Predicts You Want Snails for Dinner

At one point or another, we have all suffered from menu confusion: the feeling when a restaurant offers too many good-looking dishes, overwhelming us with choice. You don’t want to choose the wrong thing and be stuck with it, but you need to make a decision.

Bangalore-based startup dishq is using AI and consumer data to try and simplify the process by giving companies like restaurants, office cafeterias, and food delivery services the power to make personalized food recommendations to their customers.

In preparation for SKS Europe this June in Dublin, we decided to ask dishq co-founder and CEO Kishan Vasani a few questions about how his company is trying to simplify the food decision-making process.

Read the full Q&A on our Smart Kitchen Summit blog to learn about how the company uses AI to personalize your restaurant recommendations, the future of predictive ordering, and what Vasani predicts that I want for dinner. (Hint: he was (partially) right.)

If you want to hear Kishan Vasani speak more about how AI and predictive ordering will shape our eating patterns, make sure to get your tickets for SKSEurope in Dublin June 11-12th. 

Dishq Uses Machine Learning for Bespoke Food Recommendations

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.