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Halla I/O

May 15, 2019

Halla Raises $1.4M Seed Round, Pivots to Focus on AI-Powered Grocery Recommendations

Halla, a startup that uses machine learning and AI to power food recommendations for grocery shoppers, announced today that it has raised a $1.4 million seed round led by E&A Venture Capital with participation from SOSV. This brings the total amount of money Halla has raised to $1.9 million.

Halla has a B2B platform dubbed Halla I/O that helps recommend relevant food products to shoppers. As we wrote at the time of Halla’s launch last year, the “company created an entirely new model and a new taxonomy that doesn’t just look at what a food item is, but also the molecules that make it up, a map of attributes linked to other food as well as how people interact with that food.”

So if you are using a grocer’s app with Halla I/O built in, the app will serve up intelligent recommendations as you continue to shop online. Buy salt, it could recommend pepper. By salt and noodles and beef, and it might guess that you are making a bolognese and recommend tomato sauce.

If you read our coverage of Halla last year, you’d notice something different about the company now. Initially, its go-to market strategy included both grocery stores and restaurants. But in the ensuing year, Halla has abandoned its pitch to restaurants, choosing instead to focus exclusively on grocery retail.

“What we’ve found is that the market timing was screaming ‘where tech meets grocery,'” Halla Co-Founder and CEO Spencer Price told me by phone recently, “The restaurant space is more crowded for building recommendations.”

But all that work in the restaurant space didn’t go to waste. “The truth is we were able to keep all of our learnings from restaurant and made our grocery recommendations stronger,” Price said. “One core learning is that restaurant dishes and menu items, as long as they have descriptions, are just recipes without instructions.”

Halla now has more than 100,000 grocery items and one hundred million unique grocery transactions from retailers across the country in its data set, informing its machine learning algorithms. Price is quick to point out that Halla does not have any personally identifiable information on people. “We can make recommendations to customer X without knowing who customer X is,” Price said

Though a grocery chain can move a lot of product and provide a lot of data for better purchasing recommendations, grocery chains as a whole do not move quickly. To get them to adopt a new technology is like turning a battleship — they need a lot of time to execute. “They’re not looking for speed,” Price said, “but a reliable solution.”

To this end, the biggest thing Halla’s funding buys them is time. “We’ve bought some runway,” said Price. The company now has some breathing room to take its time and conduct even more tests with slow-moving retailers. Halla is in tests with unnamed grocers right now, and offers its recommendation on an API pay-per-call model.

AI-based B2B food recommendation is almost its own mini-industry. Spoonshot, Analytical Flavor Systems, and Tastewise all use vast data sets to make product predictions and recommendations to restaurants and CPG companies. Other companies like AWM Smart Shelf are using a combination of prediction and smart digital signage to make in-store grocery purchase recommendations.

With online grocery shopping reaching a tipping point, people buying food via apps adding one or two more items to their cart because of intelligent recommendations could mean a nice sales boost for the grocery industry.

July 30, 2018

Halla Launches AI-Powered B2B Food Recommendation Platform

Let’s say you’ve bought a chicken sandwich. Based just on that purchase, what do you think is a better recommendation for another meal you might enjoy: chicken piccata, or a hamburger?

This is a typical type of problem that LA-based startup, Halla, is trying to solve with its new artificial intelligence (AI) powered recommendation platform. The new Halla I/O (which stands for “Intelligent Ordering”) software integrates with a restaurant or grocer’s existing website or app, so it’s invisible to the end user. People buying groceries or meals through those apps would continue to do so, but would receive recommendations through Halla’s algorithm.

Halla I/O does this, according to Co-Founder and CEO Spencer Price, by combining data and psychographics around how people think and interact with food. Let’s go back to the chicken sandwich example. According to Price, a traditional data science approach would recommend chicken piccata, because it’s, well, chicken.

But, “The human experience of eating food is different,” Price said. He went on to describe how the chicken sandwich is also meat-centered, covered on both sides with bread and eaten by hand. And when you think of it that way, a hamburger recommendation makes sense.

Price didn’t say that the chicken piccata was wrong, per se, but just provided it as an example to illustrate how Halla I/O’s AI works differently. Using a proprietary dataset from more than 10,000 grocery items, 20,000 ingredients, 175,000 recipes and 20 million restaurant dishes, Price said that his company has created an entirely new model and a new taxonomy that doesn’t just look at what a food item is, but also the molecules that make it up, a map of attributes linked to other food as well as how people interact with that food.

With that information, Price said Halla I/O can provide more contextual and more meaningful recommendations. On a surface level, this means Halla I/O can make very basic recommendations. If you are buying salt, it might recommend pepper. But if you put salt and ground beef and onions into your cart, Halla I/O might infer that you’re making a bolognese. Not only will it recommend more items needed to make a bolognese, Halla I/O will show you recommended recipes and automatically add all the ingredients for that recipe to your cart. If you’ve shopped with that app before, Halla I/O will know if you purchased tomato sauce recently, and automatically remove that from the recommendation.

Though Halla I/O works for both restaurants and grocers, right now Halla I/O is only in pilot programs with four grocers. Interestingly, one of the pilots was with Green Zebra in Portland OR. Instead of online cart recommendations, Halla provides shelf recommendations. For example, they may see that lots of people are buying bananas and peanut butter, and set up a physical display to take advantage of that.

Halla is at the nexus of two trends we’re following at The Spoon: personalization and shoppable recipes. If its software works as promised, not only will it deliver better recommendations, but the ability to automatically recommend and adjust cart items based on recipes could be another step towards customized meal kits.

Halla is just seven employees, and has raised $500,000 in angel funding. It’s going to need more than a scrappy startup spirit, however, as the AI-powered recommendation space has plenty of competition. Startups like Dishq, Foodpairing and Plantjammer are all running their own algorithms to deliver more relevant recommendations.

Pretty soon, grocers and restaurants will need an AI-based recommendation engine to recommend the best AI-based recommendation engine.


An earlier version of this article stated that Green Zebra does not have online ordering capabilities. The grocer does through Instacart, and we have updated the post.

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