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Nothing is hotter than retail AI startups that can help stores win big this holiday shopping season.
According to eMarketer, retailers are turning to artificial intelligence to tackle everything from supply chain challenges and price optimization to self-checkout and fresh food. And retail AI is a massive, fast-growing segment filled with AI startups looking to break into a market that is estimated to hit over 40 billion by 2030.
These are seven of the hottest retail AI startups that are helping retailers meet their holiday goals:
Afresh: The retail AI startup solving for fresh food
Founded in 2017, San Francisco-based Afresh has been on a tear this year, raising a whopping $115 million in August. Afresh helps thousands of stores tackle the complex supply chain questions that have always existed around the perimeter of the supermarket — with its fruits, vegetables, fresh meat and fish. That is, how can stores make sure they have enough perfectly ripe, fresh foods available, while minimizing losses and reducing waste from food that is past its prime?
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According to a company press release, Afresh is on track to help retailers save 34 million pounds of food waste by the end of 2022. It uses AI to analyze a supermarket’s previous demand and data trends, which allows grocers to keep fresh food for as little time as possible. The platform uses an algorithm to assess what is currently in the store, with a “confidence interval” that includes how perishable the item is. Workers help train the AI-driven model by periodically counting inventory by hand.
AiFi: retail AI-powered cashierless checkout
Santa Clara, California-based AiFi offers a frictionless and cashierless retail AI-powered solution deployed in diverse locations such as sports stadiums, music festivals, grocery store chains and college campuses. Steve Gu cofounded AiFi in 2016 with his wife, Ying Zheng, and raised a fresh $65 million in March. Both Gu and Zheng have Ph.D.s in computer vision and spent time at Apple and Google.
AiFi deploys AI models through numerous cameras placed across the ceiling, in order to understand everything happening in the shop. Cameras track customers throughout their shopping journey, while computer vision recognizes products and detects different activities, including putting items onto or grabbing items off the shelves.
Beneath the platform’s hood are neural network models specifically developed for people-tracking as well as activity and product recognition. AiFi also developed advanced calibration algorithms that allow the company to re-create the shopping environment in 3D.
Everseen: AI and computer vision self-checkout
Everseen has been around since 2007, but 2022 was a big year for the Cork, Ireland-based company, which offers AI and computer vision-based self-checkout technology. In September, Kroger Co., America’s largest grocery retailer, announced it is moving beyond the pilot stage with Everseen’s solution, rolling out to 1,700 grocery stores and reportedly including it at all locations in the near future.
The Everseen Visual AI platform captures large volumes of unstructured video data using high-resolution cameras, which it integrates with structured POS data feeds to analyze and make inferences about data in real-time. It provides shoppers with a “gentle nudge” if they make an unintentional scanning error.
It hasn’t all been smooth sailing for Everseen: In 2021, the company settled a lawsuit with Walmart over claims the retailer had misappropriated the Irish firm’s technology and then built its own similar product.
Focal Systems: Real-time shelf digitization
Burlingame, California-based Focal Systems, which offers AI-powered real-time shelf digitization for brick-and-mortar retail, recently hit the big time with Walmart Canada. The retailer is rolling out Focal Systems’ solution, which uses shelf cameras, computer vision and deep learning, to all stores following a 70-store pilot.
Founded in 2015, Focal Systems was born out of Stanford’s Computer Vision Lab. In March, the company launched its FocalOS “self-driving store” solution, which automates order writing and ordering, directs stockers, tracks productivity per associate, optimizes category management on a per store basis and manages ecommerce platforms to eliminate substitutions.
According to the company, corporate leaders can view any store in real-time to see what their shelves look like and how stores are performing.
Hivery: Getting store assortments right
South Wales, Australia-based Hivery tackles the complex challenges around battles for space in brick-and-mortar retail stores. It helps stores make decisions around how to use physical space, set up product displays and optimize assortments. It offers “hyper-local retailing” by enabling stores to customize their assortments to meet the needs of local customers.
Hivery’s SaaS-based, AI-driven Curate product uses proprietary ML and applied mathematics algorithms developed and acquired from Australia’s national science agency. They claim a process that takes six months is reduced to around six minutes, thanks to the power of AI/ML and applied mathematics techniques.
Jason Hosking, Hivery’s cofounder and CEO, told VentureBeat in April that Hivery’s customers can make rapid assortment scenario strategies simulations around SKU rationalization, SKU introduction and space while considering any category goal, merchandising rules and demand transference. Once a strategy is determined, Curate can generate accompanying planograms for execution.
Lily AI: Connecting shoppers to products
Just a month ago, Lily AI, which connects a retailer’s shoppers with products they might want, raised $25 million in new capital – no small feat during these tightening times.
When Purva Gupta and Sowmiya Narayanan launched Lily AI in 2015, the Mountain View, California-based company looked to address a thorny e-commerce challenge – shoppers that leave a site before buying. Now, the company’s product attributes platform injects an enriched product taxonomy across the entire retail stack, improving on-site search conversion, personalized product discovery and demand forecasting.
For customers that include ThredUP and Bloomingdales, Lily AI uses algorithms that analyzes the retailer’s existing and future product catalog. For example, Lily will capture details about a brand’s product style and fit and expand the taxonomy to ensure that products are easily found, recommended and purchased.
Shopic: One of several smart cart retail AI startups
Tel Aviv-based Shopic has been making waves with its AI-powered clip-on device, which uses computer vision algorithms to turn shopping carts into smart carts. In August, Shopic received a $35 million series B investment round.
Shopic claims it can identify more than 50,000 items once they are placed in a cart in real time while displaying product promotions and discounts on related products. Its system also acts as a self-checkout interface and provides real-time inventory management and customer behavioral insights for grocers through its analytics dashboard, the company said. Grocers can receive reports that include aisle heatmaps, promotion monitoring and new product adoption metrics.
Shopic faces headwinds, though, with other AI startups in the smart cart space: Amazon’s Dash Carts are currently being piloted in Whole Foods and Amazon Fresh, while Instacart recently acquired Caper AI.
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