The startup develops a supply chain platform that utilizes artificial intelligence and machine learning to generate item-level demand forecasts for perishable goods in retail and wholesale environments. This technology enables clients to optimize inventory replenishment, reduce waste, and enhance profitability through precise data-driven insights.
Funding
$147.9M 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.
WRFounders
Product
Problem
Grocery retailers face challenges in accurately forecasting demand and managing inventory for fresh, perishable goods due to variable data, spoilage, and complex supply chains. Inaccurate inventory counts lead to overstocking, increased waste, and reduced profit margins, while understocking results in lost sales opportunities and dissatisfied customers.
Solution
Afresh provides an AI-powered platform that optimizes ordering, forecasting, and inventory management specifically for fresh food departments. The platform leverages machine learning, including hidden Markov models and neural networks, to account for factors like perishability, promotions, and seasonality, providing accurate, real-time insights. By integrating data across the supply chain, Afresh enables grocery retailers to make smarter decisions, reduce waste, improve shelf life, and increase sales. The system's inventory estimator (InvHMM) uses probabilistic modeling to improve inventory accuracy, quantify uncertainty, and focus store team engagement on high-value activities.
Target Audience
The primary target audience includes grocery retailers, supermarkets, and food distributors seeking to optimize their fresh food supply chain, reduce waste, and improve profitability.
Features
- AI-powered demand forecasting using deep neural networks that consider historical demand, seasonality, pricing, and promotions
- Inventory estimator (InvHMM) that leverages hidden Markov models to improve inventory accuracy and account for unrecorded shrink
- Automated store ordering based on holistic scenario testing, including sales data, perishability, and delivery schedules
- Integration with existing systems to streamline data flow and improve decision-making
- Mobile apps for store teams to manage inventory, review recommendations, and manage merchandising
- Real-time alerts and notifications to address potential stockouts or overstocking situations
- Reporting and analytics dashboards to track key performance indicators (KPIs) and identify areas for improvement
- Support for a wide range of fresh food categories, including produce, meat, seafood, deli, and prepared foods