The retail industry is undergoing a transformative shift, driven by the integration of artificial intelligence (AI) into core business operations. While flashy consumer applications of generative AI have garnered attention, a new wave of retail tech startups is focusing on addressing longstanding challenges within the sector. These innovative companies, recently highlighted in RETHINK Retail’s “Top AI Leaders in Retail for 2025,” are paving the way for the future of retail technology.
1. Bridging the Consumer-Product Language Gap with AI
One major obstacle plaguing retailers is the disconnect between how products are described by merchants and how consumers search for them. This misalignment results in lost sales and missed opportunities worth billions of dollars. Two standout companies are tackling this issue from unique perspectives.
Lily AI, catering to mid-market and enterprise retailers, addresses the “missing consumer narrative” identified by founder Purva Gupta. By incorporating emotional detail and unique perspectives gleaned from consumer interviews, Lily AI’s Product Content Optimization platform enriches product catalogs with consumer-centric language and attributes. This structured data layer enhances both frontend discovery and backend operations, leading to significant improvements in sales, ad impressions, and site traffic across fashion, beauty, and home decor categories.
On the other hand, Vody focuses on real-time search interpretation, catering to enterprise retailers seeking to enhance product discovery through multimodal generative AI. By understanding current cultural context and trending topics, Vody ensures that customers receive accurate search results, even interpreting search intent in the moment. This approach helps retailers capture high-intent traffic without the need for continuous manual updates to product data.
2. Optimizing Inventory Management with AI
Traditional retail operations often suffer from outdated inventory models and manual processes, resulting in inefficiencies and wastage, particularly in fresh food categories. Nextail is revolutionizing inventory management in the fashion industry by leveraging AI to transform static top-down inventory models. Through hyper-localized demand forecasting and automated decision-making, Nextail provides retailers with store-specific stocking recommendations based on unique fashion retail patterns. This data-driven approach replaces the reliance on high-level sales data and manager intuition, enabling retailers to make precise inventory allocations.
In the realm of grocery retail, Cognitiwe’s WeFresh platform targets enterprise-level grocery retailers and supermarket chains facing the challenge of fresh food waste. By utilizing AI-powered computer vision to monitor fresh food conditions in real-time via existing store cameras, WeFresh empowers retailers to proactively adjust prices, optimize restocking, and rotate products before spoilage occurs. This innovative solution not only addresses the €4 billion-plus waste problem but also streamlines fresh food management in complex environments.
3. Rethinking Pricing and Promotions with AI
Traditional pricing and promotion strategies often rely on manual processes and broad discounting tactics that can erode margins without optimizing revenue potential. Quicklizard’s dynamic pricing platform, designed for medium to large retailers managing extensive SKU catalogs, automates pricing decisions across product ranges. By utilizing an open AI platform that facilitates the implementation of diverse pricing strategies through simple Python code, Quicklizard enables retailers to optimize pricing dynamically. With machine learning modules analyzing factors like price elasticity and competitor behavior, retailers can enhance pricing strategies in real-time across their entire catalog.
RevLifter, targeting mid-market retailers, is disrupting the promotion landscape by delivering personalized promotions based on behavioral data and customer segments. Sitting between basic promotion platforms and premium enterprise solutions, RevLifter’s approach offers retailers a strategic edge in the highly competitive retail landscape. By leveraging advanced algorithms to analyze consumer behavior and tailor promotions accordingly, RevLifter helps retailers maximize the impact of their promotional initiatives.
4. Automating Creative Content Generation with AI
The growing demand for visual content in retail, particularly within fashion and marketing sectors, has created bottlenecks for retailers seeking to streamline workflows. Fashable, serving mid-market and enterprise retailers, leverages AI to generate photorealistic fashion imagery that accelerates the production process from concept to market. By creating exclusive AI-generated fashion visuals, Fashable enables retailers to gauge market response before committing to physical production, reducing sample waste and expediting time-to-market cycles.
Meanwhile, Rocketium addresses the scaling challenge of creating and adapting marketing creative for enterprise brands advertising on various digital platforms. With a platform that automates the creation of multiple creative versions for each campaign element while predicting performance potential, Rocketium streamlines content adaptation for different platforms and placements. Designed specifically for retail advertisers, Rocketium empowers brands to scale their creative output efficiently without the need for expansion.
The Future of Retail Tech
These pioneering AI-driven solutions signify a pivotal transformation in retail AI, emphasizing the significance of AI in revolutionizing core retail operations. While consumer-facing AI applications like Amazon’s Rufus shopping assistant have garnered attention, the true impact of AI lies in solving specific business challenges through innovative solutions. As the retail landscape evolves, these startups provide a roadmap for leveraging AI capabilities effectively. By focusing on language optimization, intelligent inventory management, dynamic pricing, and automated content creation, retailers can address key operational areas with measurable impact, positioning themselves for success in an increasingly competitive market.
These solutions go beyond mere automation, showcasing AI’s potential to solve complex problems that previously eluded traditional approaches. Whether it’s Lily.ai facilitating communication between retailers and consumers or WeFresh predicting fresh food spoilage in advance, these platforms underscore AI’s ability to drive tangible business outcomes. While chatbots and recommendation engines have their place, the future of retail technology lies in targeted solutions that deliver meaningful results, reshaping the industry from within.