According to the Environmental Protection Agency, over 85% of greenhouse gas emissions from landfilled food waste stem from errors that happen before the food ever arrives at a consumer’s plate—spanning production, processing, and distribution. FloVision AI (formerly FloWaste), a USA-based startup founded by Irishman Rian Mc Donnell, is tackling food system inefficiency at the processing stage through a proprietary machine learning system.
FloVision AI announced today that it has secured a $1.1M pre-seed funding round, which will be used to expand and refine its technology. Last week, The Spoon connected via Zoom with company founder and CEO Rian Mc Donnell to learn how FloVision AI can help food producers divert more food from landfills.
Mc Donnell conceived the idea for FloVision AI while pursuing mechanical and manufacturing engineering at Trinity College Dublin. “I was drawn to the subject of food waste because by that stage, I understood that whatever path I chose, my career would be centered on sustainability,” says Mc Donnell.
Here’s how FloVision AI operates: Customers select 20 food items they want the system to monitor, and the team trains their machine learning system to identify those foods. The team then positions cameras above customers’ workstations, production lines, and waste bins. The cameras observe the food production process, automatically categorizing food items and measuring how much is discarded.
Video: FloVision AI food identification and classification. Source: FloVision AI
“We collect an enormous amount of data,” says Mc Donnell. “And we can slice and analyze that data by ingredient usage, yield, shift performance, or daily output. We deliver those insights to management, enabling them to implement procedural improvements.”
The technology is applicable across both the industrial and commercial food sectors. One of FloVision AI’ current clients, a leading European protein producer, is deploying the system to track waste on a beef production line. “There’s a significant financial return because proteins are costly,” says Mc Donnell, “but also a substantial environmental return because any improvement in yield means you’re effectively processing fewer cattle over time.”
According to Mc Donnell, the process of training the machine learning system to identify various foods has been labor-intensive. However, he anticipates that as the system accumulates knowledge, scaling its application will become progressively simpler. “If we work with someone processing fries, it means the next time we encounter fries, we already have a foundation to build on,” he says. “We’re steadily gathering more data to the point where eventually we’ll be able to handle a universal use case encompassing food as a whole.”
This pre-seed funding round will enable FloVision AI to scale its technology: The company has executed agreements to deploy the system at over 100 locations with its pilot customers within the next nine months. The funding will also assist the team in overcoming the challenges of building a hardware system from the ground up using off-the-shelf cameras. In the near term, Mc Donnell plans to recruit a full-time IoT engineer to make the system more streamlined and dependable.
FloVision AI is taking part in the current cohort of Rockstart’s Agrifood accelerator. Mark Durno, Managing Partner AgriFood, Rockstart states:
“Reducing food loss and waste is critical if we are to operate within planetary boundaries while still nourishing over 9 billion people by 2050. Beyond being impressed by the team, we invested because FloVision AI is not merely addressing a symptom—their solution spans the entire value chain, positioning them to serve as the waste reduction engine for a fragmented industry.”
The company has additionally secured funding from U.S. venture funds, including Underdog Labs and Flywheel Fund.
Over the longer term, the team aims to grow through new partnerships. “We’re working on installations in cafeteria kitchens and providing post-consumer analytics for customers who require that,” says Mc Donnell. “And we’re exploring quick-service restaurants because they place such strong emphasis on optimizing their processes and food yield in the kitchen.”
At its core, the company is dedicated to helping food producers recognize how more environmentally responsible processes can also strengthen margins. “The most effective way to achieve a sustainability benefit is to link it to the financial performance of a business,” says Mc Donnell, “and demonstrate to companies how they can generate greater revenue by operating more sustainably.”
About Rockstart
Rockstart is a global accelerator-VC that supports purpose-driven founders across three domains: Energy, AgriFood and Emerging Technologies. Rockstart offers startups access to capital, markets, community, and expertise by linking them with investors, mentors, partners, and the broader Rockstart network.
Since its founding, Rockstart has invested in more than 250 startups, with its alumni value to date exceeding €750m. Rockstart comprises an international team of over 35 professionals committed to enabling purpose-driven founders to achieve scale and create positive global change. Rockstart has notable exits such as Wercker, Bouw7, iClinic, and in 2021, 3D Hubs and Brincr. The company has offices in Amsterdam, The Netherlands, Copenhagen, Denmark and Bogota, Colombia.
SOURCE The Spoon
View original content: https://thespoon.tech/flowaste-raises-a-1-1m-pre-seed-round-to-reduce-food-waste-with-machine-learning/