Company Performance Metrics
RNV.ai is an AI-powered retail decision intelligence platform that helps fashion, apparel, footwear, and lifestyle retailers optimize inventory, allocation, pricing, and merchandising decisions across the entire product lifecycle.
RNV combines artificial intelligence, predictive analytics, and retail expertise to help brands reduce stockouts,
improve sell-through, increase full-price sales, and maximize profitability in fast-changing demand environments.
The platform enables retailers to move from reactive planning to real-time, data-driven decision-making through a suite of AI-powered products, including: -Preseason Planning: AI-assisted demand forecasting and assortment planning to improve buy accuracy, category performance, and inventory investment decisions before the season starts. -Allocation & Replenishment: Dynamic inventory allocation and automated replenishment recommendations based on real-time sales, regional demand, store performance, and product trends. -Pricing & Markdown Optimization: Intelligent pricing and markdown strategies designed to protect margins, accelerate sell-through, and reduce excess inventory. -Merchandising Intelligence: Actionable insights for merchandising teams to identify winning products, optimize assortments, and improve in-season performance. -Store & Regional Performance Analytics: AI-driven visibility into store clustering, local demand behavior, and product performance variations across channels and geographies. -Retail AI Agents: Autonomous AI agents that continuously monitor inventory, sales, and demand signals to recommend or automate critical retail decisions.
RNV integrates with retailers’ existing ERP, e-commerce, and planning systems, enabling fast deployment and measurable business impact within weeks rather than months.
The company works with retailers seeking to modernize traditional merchandising and planning processes with scalable AI technology, helping them operate with greater agility, efficiency, and profitability in an increasingly competitive retail landscape.