
Refraction AI
Building and deploying robotic platforms for providing safe and scalable last mile goods delivery in urban areas.
Date | Investors | Amount | Round |
---|---|---|---|
- | investor investor | €0.0 | round |
investor investor | €0.0 | round | |
investor | €0.0 | round | |
investor investor investor investor investor investor investor | €0.0 | round | |
N/A | Seed | ||
Total Funding | 000k |
USD | 2019 | 2020 | 2022 | 2023 |
---|---|---|---|---|
Revenues | 0000 | 0000 | 0000 | 0000 |
% growth | - | 165 % | - | 10 % |
EBITDA | 0000 | 0000 | 0000 | 0000 |
Profit | 0000 | 0000 | 0000 | 0000 |
EV | 0000 | 0000 | 0000 | 0000 |
EV / revenue | 00.0x | 00.0x | 00.0x | 00.0x |
EV / EBITDA | 00.0x | 00.0x | 00.0x | 00.0x |
R&D budget | 0000 | 0000 | 0000 | 0000 |
Source: Dealroom estimates
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Refraction AI, an autonomous logistics firm, was established in 2017 by Matthew Johnson-Roberson and Ram Vasudevan, both professors at the University of Michigan with deep backgrounds in robotics and autonomous systems. Johnson-Roberson has been involved in robotics since the first DARPA Grand Challenge and specializes in computer vision and artificial intelligence for autonomous vehicles. Vasudevan is an associate professor in Mechanical Engineering and Robotics at the University of Michigan, focusing on optimization and control of autonomous systems. Their combined academic and research experience in real-world robotics applications formed the foundation of the company.
The company operates on a Robot-as-a-Service (RaaS) and Delivery-as-a-Service (DaaS) model, targeting the last-mile delivery market for restaurants, grocery stores, and retail businesses. Its primary product is the REV-1, a lightweight, three-wheeled autonomous delivery robot. The REV-1 is designed to be cost-effective, a goal achieved by using 12 cameras and other low-cost sensors for navigation instead of expensive LiDAR systems. This design allows the robot to operate in various weather conditions, including rain and snow, a key consideration tested during its development in Michigan. The vehicle is sized to travel in bike lanes and on the roadway, avoiding sidewalk congestion, and can move at speeds up to 24 km/h.
Refraction AI's business strategy focuses on making last-mile delivery profitable and sustainable, claiming its method reduces carbon emissions by 90% and energy consumption by 80% compared to conventional delivery. Customers of client businesses receive a unique pin code via text to access their orders from the robot's 16-cubic-foot cargo compartment upon its arrival. The company began pilot programs in Ann Arbor, Michigan, in 2019, later expanding to Austin, Texas. A significant milestone was a partnership with Chick-fil-A to test autonomous delivery at several of its restaurants. The company secured $4.2 million in a seed funding round in March 2021 to fuel expansion and product development.
Keywords: last-mile delivery, autonomous robots, robot-as-a-service, REV-1, delivery logistics, Matthew Johnson-Roberson, Ram Vasudevan, University of Michigan spin-out, restaurant delivery, grocery delivery, retail logistics, sustainable delivery, autonomous vehicle technology, computer vision navigation, urban delivery solutions, Chick-fil-A partnership, Ann Arbor robotics, Austin delivery, RaaS, DaaS