News Commentary | February 03, 2020
IMAGR's carts use computer vision to recognize items in the carts, so IMAGR provides consumers real‑time updating receipts via phone app and automatically charges consumers from their accounts when they walk out from retail stores. IMAGR is poised to grow in Japan, as its investor Toshiba Tec ... Not part of subscription
Case Study | October 13, 2020
Retail food waste is a leading contributor to food loss and waste in developed countries. In light of this, there is a pressing need for retail players to take a multifaceted approach to reducing food waste, including increasing the shelf life stability of food products and managing their supply ... Not part of subscription
News Commentary | November 03, 2020
Since its founding in 2015, Freshly has reportedly grown every year and is now delivering more than a million meals per week across the U.S., with 2020 sales forecasted to be $430 million. There are two plausible reasons for Freshly's success. The first is its focus on prepared meals (rather than ... To read more, click here.
by Harini Venkataraman
This funding round was led by Innovation Endeavors, with participation from Food Retail Ventures, Maersk Growth, and other investors. Afresh develops machine learning algorithms that help improve inventory management of fresh foods including produce, meat, and dairy products on retail shelves, with the stated goal of reducing food waste. The company is looking to partner with more U.S. grocers to expand its customer base. As Lux outlined in its recent report, clients should expect to see increased adoption of digital tools to mitigate food waste in the distribution and retail segments, driven by the digital transformation of supply chain management.
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