# Focal Systems Named Emerging Retail Technology Innovation of the Year at the 2026 RTIH Innovation Awards - Published: 2026-11-09 - Author: [Retail News](https://retailnews.io/author/retailnews-io.md) - Topics: [News](https://retailnews.io/news.md) - Source: https://retailnews.io/news/focal-systems-named-emerging-retail-technology-innovation-of-the-year-at-the-2026-rtih-inn/ - Publication: Retail News - Publisher: Connectively (Terkel, Inc.) - Editorial policy: https://retailnews.io/editorial-policy/ *Shelf intelligence company also shortlisted for Technology Vendor of the Year (UK) and Best Data Analytics Driven Retail Initiative* **Our technology is revolutionising the way our partner retailers manage inventory, improve sales, and minimise shrinkage every day.”** — Kevin Johnson, CEO LONDON, UNITED KINGDOM, November 9, 2026 /[EINPresswire.com](https://www.einpresswire.com/)/ -- [Focal Systems](http://focal.systems), the AI-powered shelf intelligence company, has won Emerging Retail Technology Innovation of the Year at the [2026 RTIH Innovation Awards](https://retailtechinnovationhub.com/home/2026/11/5/morrisons-waitrose-and-dunelm-take-top-honours-at-2026-rtih-innovation-awards-ceremony-in-london). The category is new this year and recognises emerging technologies that have moved past proof of concept and are delivering results for retailers at scale. Focal was also a finalist in two further categories: Technology Vendor of the Year (UK) and Best Data Analytics Driven Retail Initiative. Winners were chosen by a [judging panel](https://retailtechinnovationhub.com/2026-rtih-innovation-awards-judging-panel) of retail and brand leaders from businesses including Walmart, Amazon, JD Sports Fashion, Holland & Barrett, CVS Health, Batteries Plus and East of England Co-op. Focal's fixed cameras photograph every shelf in store every hour, report gaps as they appear, and action their replenishment with products in inventory. In 2026 the company extended that view to the stock stacked above the shelf. The system now matches an empty shelf to stock the store already holds, turns it into a task for the right hour of the day, and uses the same cameras to confirm the gap was filled. To date, Focal's cameras have confirmed more than 23 million shelf gaps filled. At Morrisons, where Focal covers almost 500 supermarkets, the time to spot an empty shelf has fallen from 12–24 hours to around 30 minutes. On-shelf availability is up 2–4%, and shelf accuracy has risen from 65% to 95%. "We are thrilled to be recognised by the Retail Technology Innovation Hub for the advances we’ve made in Shelf AI," said Kevin Johnson, CEO of Focal Systems. "Our technology is revolutionising the way our partner retailers manage inventory, improve sales, and minimise shrinkage every day. This year we are pleased to bring to market added innovations in top stock management as well as theft identification and reduction." The win follows Focal's In-Store Technology of the Year award at the Retail Systems Awards in June 2026 and its place on RTIH's Hot 100 list for 2026. Focal previously won RTIH's Digital Transformation award in 2024 for its Morrisons rollout as well as Grocer Gold in 2025 for Technology Initiative of the Year. About Focal Systems Headquartered in San Francisco, Focal Systems (Focal), the leader in Shelf AI for retail operations, is an AI-powered retail automation platform revolutionising how stores operate. Built to solve one of retail’s most persistent challenges—keeping shelves stocked and customers satisfied—Focal combines computer vision, deep learning, and real-time data streaming to maximise product availability and store productivity while controlling inventory costs. Focal conducts over 40 million shelf scans per day to empower the world’s leading retailers to reduce waste, improve margins, and elevate the shopping experience at scale. Jenna Black Focal Systems Visit us on social media: [LinkedIn](https://www.linkedin.com/company/focal-systems-inc./) Legal Disclaimer: EIN Presswire provides this news content "as is" without warranty of any kind. We do not accept any responsibility or liability for the accuracy, content, images, videos, licenses, completeness, legality, or reliability of the information contained in this article. 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