7 AI startups aim to give retailers a happy holiday season

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Nothing is hotter than artificial intelligence (AI) startups that can help retailers 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 AI startups that are helping retailers meet their holiday goals: 

Afresh: The 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: AI-powered cashierless checkout

Santa Clara, California-based AiFi offers a frictionless and cashierless AI-powered retail 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. 

For customers that include ThredUP and Everlane, Lily AI uses algorithms that combine deep product tagging with deep psychographic analysis to power a web store’s search engines and product discovery carousels. For example, Lily will capture details about a brand’s product style and fits and use customer data from other brands to create a prediction of a customer’s affinity to attributes of products in the catalog. 

Shopic: One of several smart cart 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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Report: 81% of online retailers increase AI budget to boost holiday sales

The nation’s online retailers, bullish on holiday sales but worried about supply chain disruptions, are increasing their investments in artificial intelligence systems to help manage operations and increase sales. The move will also help them compete with online giants like Amazon.

Eighty-five percent of retailers expect online sales to increase during the 2021 holiday shopping season, continuing an upward trend from the pandemic lockdowns of 2020, according to the 2021 eCommerce Outlook Report from Anodot and Researchscape. However, 42% of retailers remain concerned about the impact supply chain disruptions are likely to have on inventories and the timely delivery of their products.

Supply chain disruptions and labor shortages are affecting retailers around the globe, prompting many to launch their holiday sales early this year amid concerns that inventory won’t hold up for the duration of the season. Factory closings, a shortage of port workers and truck drivers, and a scarcity of key product components such as microchips have raised fears of short supplies and rising prices.

To help them stay competitive, retailers are turning to artificial intelligence, with 81% of the merchants in the survey saying they planned to increase their AI budgets this year. In addition to AI-enhanced protections such as fraud detection, retailers are looking to AI to help drive growth, with a third of respondents predicting that AI can increase revenues by 40%.

“Retailers need AI to create a flawless purchasing experience,” said David Drai, CEO and founder of Anodot, noting the mix of both uncertainty and optimistic holiday expectations. “Otherwise, shoppers will simply turn to the bigger retailing behemoths or the next online retailer to get their gifts.”

AI is becoming an essential tool in ecommerce, for uses such as making real-time recommendations, enabling targeted campaigns, and improving supply chain management. Online retailers said their top priorities this year are inventory, pricing, and website experience.

The survey was conducted during the month of September, and involved 106 respondents, 91% of whom identified themselves as being in the ecommerce industry.

Read the full report by Anodot and Researchscape.


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Some Retailers Shipping Alder Lake CPUs, and They’re Cheap

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Intel has promised that its 12th-gen Alder Lake platform is arriving in 2021, but the company has yet to announce an official release date. It seems some retailers are getting antsy, and have even shipped processors to customers weeks ahead of the rumored launch date.

Reddit user u/Seby9123 apparently received two Intel Core i9-12900K processors, two weeks ahead of the rumored release date. We always recommend handling random Reddit posts with skepticism, but the images of the processor and its box are hard to argue with. The user posted images of the Core i9-12900K — there’s no arguing with that.

You can see a few of the images above detailing the intricacies of the packaging and the processor itself. The box lines up with a leaked render, which showed the Core i9-12900K sandwiched between a replica of a golden wafer slice.

Even more interesting than the box is the price. The original poster said they paid only $610 for each processor before tax. That’s $60 more than last-gen’s Core i9-11900K, but still $190 less than AMD’s competing Ryzen 9 5950X. If leaked benchmarks are true, Intel could be going for an aggressive price/performance target.

The price runs counter to earlier rumors, which showed the flagship chip selling for as much as $1,000. Going into this generation, price is going to play a big role as AMD continues to assert its lead in desktop processors.

We went to some popular retailer websites and, unsurprisingly, didn’t find any 12th-gen processors available. It seems this order slipped through the cracks somehow, so the original poster was able to snag a couple of chips early. They weren’t, however, able to track down a 600-series chipset motherboard to take the processors out for a spin.

Although Intel hasn’t confirmed the release date of Alder Lake, the chips should be arriving soon. Rumors point to the chips launching on November 4, though we’ve also seen rumors suggesting a November 19 launch. Regardless, we should know more soon.

Intel is set to begin its Innovation event on October 27, where we anticipate an announcement for the Alder Lake release date. The company has confirmed time and again that the chips are arriving in 2021, so we should know the specifics soon.

Editors’ Choice

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Retailers Are Charging Outrageous Prices for the RTX 3080

A report from 3D Center reveals the dire state of the graphics card market in Europe. The German outfit analyzed the prices of graphics cards from some of the top European retailers and found some are charging as much as three times the MSRP for RTX 30-series cards. AMD’s RX 6000 cards were found to be equally as expensive, with prices that range from two times to two-and-a-half times above MSRP.

The most egregious model is the RTX 3080, which launched with a list price of 719 Euros (around $880 U.S. at current rates). The “best price” for the card currently, according to 3D Center, is now 2,999 Euros, or around $3,650 — a 317% price increase.

The data gathered by 3D Center shows a steady growth in price throughout 2021, with prices hitting an all-time high on May 16, when the last data points were gathered. As executives from Nvidia warn of further shortages, we can only anticipate that the prices will continue to climb.

Nvidia cards show the clearest price gouging, but AMD cards are significantly marked up, too. The Radeon RX 6900 XT is, out of all AMD and Nvidia cards, selling closest to its list price. There’s still a 70% increase, however. The card launched for 999 Euros (around $1,200) and is now selling for as much as 1,799 Euros (around $2,200). The RTX 3070 shows a 189% increase, the RX 6800 shows a 159% increase, and even the budget-focused RTX 3060 is selling for 204% more than its list price.

It’s remarkably normal to see such insane prices for graphics cards as the GPU shortage and semiconductor shortage as a whole continues. Even our list of the best GPU deals is full of cards that are not only overpriced, but underpowered. The GTX 1050 Ti — which is a dinosaur by the GPU standards of today — is selling for close to $400, for example, which should be the price of an RTX 3060 Ti.

You can’t find a graphics card for list price anywhere. Thankfully, we have a few alternatives to buying a GPU that will save you money while allowing you to play the latest games.

Editors’ Choice

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Google launches suite of AI-powered solutions for retailers

Google today announced the launch of Product Discovery Solutions for Retail, a suite of services deigned to enhance retailers’ ecommerce capabilities and help them deliver personalized customer experiences. Product Discovery Solutions for Retail brings together AI algorithms and a search service, Cloud Search for Retail, that leverages Google Search technology to power retailers’ product-finding tools.

The pandemic and corresponding rise in online shopping threaten to push supply chains to the breaking point. Early in the COVID-19 crisis, Amazon was forced to restrict the amount of inventory suppliers could send to its warehouses. Ecommerce order volume has increased by 50% compared with 2019, and shipment times for products like furniture more than doubled in March. Moreover, overall U.S. digital sales have jumped by 30%, expediting the online shopping transition by as much as two years.

Product Discovery Solutions for Retail, which is generally available to all companies as of today, aims to address the challenges with AI and machine learning. To that end, it includes access to Google’s Choice AI, which uses machine learning to dynamically adapt to customer behavior and changes in variables like assortment, pricing, and special offers.

Choice AI, which launched in beta in July and is now generally available, ostensibly excels at handling recommendations in scenarios with long-tail products and cold-start users and items. Thanks to “context-hungry” deep learning models developed in partnership with Google Brain and Google Research, it’s able to draw insights across tens of millions of items and constantly iterate on those insights in real time.

Google Choice AI

From a graphical interface, businesses using Choice AI can integrate, configure, monitor, and launch recommendations while connecting data by using existing integrations with Merchant Center, Google Tag Manager, Google Analytics 360, Cloud Storage, and BigQuery. Choice AI can incorporate unstructured metadata like product name, description, category, images, product longevity, and more while customizing recommendations to deliver desired outcomes, such as engagement, revenue, or conversions. And it lets Google Cloud customers apply rules to fine-tune what shoppers see and diversify which products are shown, filtering by product availability and custom tags.

Product Discovery Solutions for Retail also includes access to Google’s Vision API Product Search, which allows shoppers to search for products with an image and receive a ranked list of visually and semantically similar items. Google says Vision Product Search taps machine learning-powered object recognition and lookup to provide real-time results of similar, or complementary, items from retailers’ product catalog.

Beyond Choice AI and Vision API Product Search, Product Discovery Solutions for Retail ships with Cloud Search for Retail. Cloud Search for Retail, which is currently in private preview, pulls from Google’s understanding of user intent and context to provide retail product search functionality that can be embedded into websites and mobile apps.

“As the shift to online continues, smarter and more personalized shopping experiences will be even more critical for retailers to rise above their competition,” Google Cloud retail and consumer VP Carrie Tharp said in a statement. “Retailers are in dire need of agile operating models powered by cloud infrastructure and technologies like artificial intelligence and machine learning (AI/ML) to meet today’s industry demands. We’re proud to partner with retailers around the world and bring forward our Product Discovery offerings to help them succeed.”


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