Optimizing Food Redistribution via Algorithmic Matching
Food donors have excess inventory but lack efficient distribution channels
Meal Lift's algorithmic matching connects surplus with need in real-time
Food reaches shelters efficiently, reducing waste and fighting hunger
We work with organizations across Europe and the United States to optimize food redistribution and humanitarian aid delivery. Our partners range from international aid organizations to local food recovery networks.
Quick Inventory Logging
Snap a photo, add details, and log your surplus goods in seconds
Automated Matching
Our algorithm finds the nearest shelter with matching needs
Driver Dispatch
Volunteer drivers receive automated notifications and handle pickup
NOTIFICATION PREVIEW
✓ Match found! Driver en route to pickup location
Real-Time Inventory
Shelters update their needs and capacity in real-time
Geospatial Matching
The system matches you with nearby donors based on proximity and need
Delivery Tracking
Track incoming deliveries with real-time updates and ETA
ROUTING MAP PREVIEW
Meal Lift leverages computational optimization and machine learning to solve the geospatial matching problem at scale, ensuring maximum efficiency and impact.
Voronoi diagram-based partitioning optimizes donor-recipient pairs by minimizing Euclidean distance while accounting for road network constraints.
Gradient-boosted decision trees predict optimal routing sequences, reducing delivery time by an average of 23% compared to naive nearest-neighbor approaches.
Graph-based data structures enable O(log n) updates and queries, supporting thousands of concurrent transactions with sub-100ms latency.