Milky Way AI develops a computer vision platform that provides real-time, store-level insights for FMCG and CPG companies, enabling automated stock replenishment and improved on-shelf availability. By addressing the $1 trillion annual loss due to out-of-stock issues, the platform enhances sales performance by up to 5% through efficient inventory management and competitive analysis.
Funding
$245K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
DAEFTKFounders
Product
Problem
Fast-moving consumer goods (FMCG) and consumer packaged goods (CPG) companies face significant revenue loss due to out-of-stock situations and suboptimal on-shelf availability in retail stores. Traditional methods of monitoring shelf conditions are manual, time-consuming, and lack real-time insights, hindering effective stock replenishment and merchandising strategies. This results in a substantial annual loss for retailers and brands.
Solution
Milky Way AI offers a computer vision-powered retail platform that provides real-time, store-level insights to address out-of-stock issues and improve on-shelf availability. The platform automates stock replenishment by analyzing shelf conditions and product placement using image recognition technology. By identifying products at the SKU and packaging level, including variations in flavors, pack sizes, promotions, and parallel imports, the system enables efficient inventory management and competitive analysis. The platform's AI models require significantly less training data, allowing for rapid deployment and detection of new SKUs.
Target Audience
The primary target audience includes FMCG and CPG companies, retailers, and their sales, marketing, operations, and finance teams seeking to optimize sales, improve on-shelf availability, and gain a competitive edge through real-time store-level insights.
Features
- Real-time monitoring of on-shelf availability and product placement using computer vision
- Automated identification of retail products at the SKU and packaging level
- Detection of flavor variations, pack sizes, promotions, and parallel imports
- Competitive analysis, including share of shelf and competitor promotions
- Planogram and promotion compliance monitoring
- Mobile application for field sales teams to identify and address on-shelf availability gaps
- Integration with existing retail systems for automated stock replenishment