Califrais provides an AI-powered platform to optimize fresh food supply chains, reducing waste and carbon emissions. Its integrated solutions manage inventory, orders, and deliveries, enhancing efficiency for wholesalers, distributors, and retailers.
Funding
$11.4M 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.
Founders
Product
Problem
The food supply chain faces significant challenges in efficiency and sustainability, leading to substantial food waste and high carbon emissions. Optimizing the complex logistics of fresh produce distribution at scale remains a critical hurdle for industry stakeholders.
Solution
Califrais develops AI-powered technological solutions to optimize food supply chains, focusing on decarbonization and waste reduction. The company's platform integrates various logistical functions, including marketplace and e-commerce capabilities, catalog management, inventory control, order fulfillment, delivery optimization, and tailored invoicing. By leveraging machine learning and advanced algorithms, Califrais aims to enhance operational efficiency and environmental performance across the fresh food sector. Their deployed solutions have demonstrated a significant impact, including halving food waste and reducing CO2 emissions by a factor of seven.
Target Audience
Califrais targets professionals within the food supply chain, including wholesalers, distributors, retailers, and restaurateurs, particularly those dealing with fresh and perishable goods.
Features
- AI-driven platform for optimizing food supply chain logistics, including demand forecasting, inventory management, and delivery route optimization.
- Integrated marketplace and e-commerce functionalities for streamlined procurement of fresh produce.
- Advanced catalog management (PIM) and warehouse management system (WMS) for efficient stock and order processing.
- Dynamic pricing strategies and perishable inventory optimization algorithms.
- Machine learning models for predictive analytics on customer satisfaction and operational resource allocation.
- Focus on decarbonization of logistics and reduction of food waste through data-driven insights.
- Research and development through the LabCom LOPF, a collaboration with institutions like CNRS and Sorbonne Université, focusing on convex optimization, time series analysis, and reinforcement learning for large-scale logistics problems.
- Deployment of solutions within the Rungis market, the world's largest fresh produce market, serving thousands of professionals.