Funding Momentum Puts Retail Intelligence Platforms In The Spotlight
Two recent funding rounds underscore how strongly investors now value AI-driven retail intelligence. RADAR secured USD 170 million (approx. RM782 million) in Series B funding at a USD 1 billion (approx. RM4.6 billion) valuation, backing its ambition to become a foundational retail intelligence platform. At the other end of the company lifecycle, Retailgrid raised €358,000 in pre-seed capital to modernise pricing and planning workflows for mid-market retailers. Taken together, these rounds illustrate a clear thesis in retail AI funding: capital is flowing to platforms that replace manual, spreadsheet-based processes with connected, data-rich systems. Rather than building yet another point solution, both firms promise end-to-end visibility across pricing, inventory, and assortments. For retailers, the implication is that operational excellence is shifting from labour-heavy analysis to AI-supported decision-making embedded directly in day-to-day tools.
From Spreadsheets To Smart Workbooks: Retailgrid’s Automation Bet
Retailgrid is targeting a surprisingly persistent habit in retail: running critical pricing and forecasting decisions out of Excel. Many mid-sized retailers and FMCG brands still juggle fragmented systems, manual spreadsheets, and external consultants for pricing, promotions, and inventory planning. Retailgrid’s answer is an AI-powered workbook that looks and feels familiar to spreadsheet users, but connects directly to ERP systems, e-commerce platforms, and market data feeds. Within this environment, users can call up pricing models, demand forecasts, assortment proposals, and promotion analyses via natural language prompts, while retaining transparency into the underlying data and logic. Effectively, it is pricing automation software wrapped in a spreadsheet-like interface. By embedding pre-built AI agents for price optimisation, sales forecasting, assortment planning, promotion analysis, and competitor monitoring, Retailgrid aims to cut the time, complexity, and risk associated with ad-hoc models that tend to "break" as product catalogues and data volumes grow.
RADAR Brings Real-Time Inventory Intelligence To Physical Stores
While Retailgrid focuses on analytical workflows, RADAR is reengineering store operations in real time. Its vertically integrated retail intelligence platform combines proprietary overhead sensors with software and analytics to deliver 99% item-level inventory accuracy across sales floors, stockrooms, and fitting rooms. By continuously tracking tagged items, RADAR feeds a stream of data into applications for replenishment alerts, omnichannel fulfilment routing, loss prevention, and merchandising insights. The company already processes more than 100 billion item-level events per day across over 1,400 stores, working with major apparel retailers. Investors describe this as closing a long-standing “blind spot” in the physical world, giving stores a data backbone comparable to e-commerce. As RADAR expands into autonomous checkout and enhances its AI analytics, its retail forecasting tools are positioned to help merchants not only see what is in stock, but anticipate demand and adjust assortments with a level of precision previously unavailable in brick-and-mortar environments.
Targeting Retail’s Core Pain Points: Pricing, Inventory, Assortment
The surge in retail AI funding is not about novelty; it is about attacking the most expensive operational pain points. Retailers routinely struggle with pricing optimisation, often relying on static rules or slow, consultant-led analyses instead of dynamic pricing automation software. Inventory accuracy remains stubbornly low in many stores, fuelling out-of-stocks, overstocking, and poor fulfilment decisions. Assortment planning, meanwhile, is frequently constrained by limited analytics capacity and fragmented data. Retailgrid and RADAR both tackle these issues head-on. Retailgrid automates scenario modelling around prices, promotions, and product mixes, making it easier for commercial teams to test and iterate decisions. RADAR supplies the real-time, item-level inventory visibility needed to inform those decisions on the ground, from replenishment to merchandising. Together, such platforms close the loop between planning and execution, enabling retailers to run assortments, pricing, and inventory as interconnected levers rather than isolated workflows.
What The New Wave Signals About Retail Tech Priorities
These investments send a clear message about where retail tech is heading. First, operational intelligence is becoming non-negotiable: running stores “blind” to real-time inventory or relying on brittle spreadsheets for planning is being framed as an active choice to leave money on the table. Second, usability matters. Retailgrid’s spreadsheet-like interface acknowledges that adoption hinges on meeting users where they are, not forcing them into heavyweight enterprise systems. Third, integrated data and automation are now central to competitive advantage, whether in the form of RADAR’s sensor-driven store visibility or cloud-native retail forecasting tools. For retailers evaluating their own technology roadmaps, the priority is shifting from isolated analytics projects to platforms that embed AI into daily decisions. The winners will likely be those who modernise their operational core early—turning inventory, pricing, and assortment from chronic headaches into differentiated strengths.