The global food industry faces a significant challenge: approximately one-third of all food produced is wasted. This waste contributes heavily to greenhouse gas emissions and costs producers over $200 billion annually. FloVision Solutions, a startup founded in 2020, aims to tackle this problem by minimising food waste and processing inefficiencies through advanced artificial intelligence.
FloVision recently secured an $8.7 million Series A funding round led by Insight Partners, with participation from Serra Ventures, SOSV, and Rockstart. This investment brings their total funding to $11.6 million, enabling global expansion across North America, Europe, Australia, South America, and Asia, while growing their engineering, AI/ML, and sales teams.
“We’re on a mission to reduce global greenhouse gas emissions by 1% by tackling waste at the source. The value lost in global food waste is staggering. Yet, the opportunity to recover yield and optimise quality is enormous,” explains Rian Mc Donnell, CEO and co-founder, in a conversation with TFN.
The birth of a mission: challenging the status quo
FloVision was established by Rian Mc Donnell and Elise Weimholt, whose combined expertise drives the company’s innovation. Mc Donnell’s engineering background and upbringing in rural Ireland, where his family worked in beef processing, gave him firsthand insight into protein production challenges. “I saw firsthand how yield loss and quality inconsistencies impact processors. These experiences shaped my belief that technology could revolutionise an industry that has been slow to innovate,” he says.
Elise Weimholt, CTO of FloVision, oversees all product development. Motivated by the urgent need to adapt the global economy to climate change, she identified food supply chain waste as a prime opportunity for AI-driven solutions. “Building FloVision has been about translating customer pain points into real technical solutions that make a tangible difference,” she notes.
Together, they evolved FloVision from an initial concept focused on cafeterias to a robust AI platform serving protein processing facilities worldwide. “Hundreds of customer interviews and on-site observations informed every facet of our product roadmap. This close customer connection ensures our technology targets the real problems processors face with yield measurement, quality control, and staff performance,” Mc Donnell adds.
The company maintains a hybrid, globally distributed team across the U.S. and Europe, with a strong focus on diversity and inclusion. Led by female co-founder and CTO Elise Weimholt, FloVision promotes a culture of respect and belonging. Elise reflects, “In tech, especially startups, it can be isolating as a woman. At FloVision, I found a supportive environment where my voice matters, and that makes all the difference. I encourage women entering tech to find champions and create spaces where they can be fully themselves.”
Behind FloVision: cutting-edge technology driving measurable impact
FloVision’s strength lies in its AI-driven hardware and software ecosystem. Its two main products serve different operational needs: FloVision Nano, a compact camera system that connects directly to conveyor belts, captures vision, depth, and weight data to measure products, spot defects, and analyse volumes without disrupting production. FloVision Pro enhances accuracy using a three-camera setup with dynamic laser projection, monitoring, trimming, yield, and quality at workstations while providing real-time feedback to operators.
“Our sensors don’t just gather data, they enable processors to act instantly. By detecting defects, misgrades, and foreign materials in real time, and matching products to exact customer specs, processors reduce waste and recover lost yield, up to 1.5% on average. In an industry where profit margins can be razor-thin, these gains are transformative,” Mc Donnell explains.
All data flows into a centralised dashboard that empowers supervisors to track trends, benchmark shift performance, and optimise labour efficiency. Customers have reported returns on investments as high as 15 times from reduced waste and faster decision-making. “Our technology breaks through decades of manual, error-prone practices to deliver rapid, sustained value. The ROI and environmental benefits speak for themselves,” Mc Donnell states.
FloVision views its biggest competitor not as another company, but as the industry’s entrenched “status quo.” “Too many processors accept yield loss as an unavoidable cost. We’re proving there is a better way: one grounded in precision AI analytics and real-time feedback,” says Mc Donnell.
What’s next for FloVision?
With $11.6 million in total funding and a rapidly expanding customer base processing more than 23 million kilograms of food worldwide, FloVision is poised to scale. “The next three to five years are about deepening our product capabilities, such as advanced AI to detect even subtle yield loss, and expanding globally to more protein processors,” Mc Donnell outlines. The roadmap includes enhanced quality assurance tools, sophisticated operator training features, and new staff performance analytics proven to reduce onboarding time by up to 50%.
“We want to become the largest provider of AI-enabled hardware services to the global food industry, helping processors maximise yield, ensure quality consistency, and enhance labour productivity at an unprecedented scale. This ambition aligns with our environmental mission: Reducing food waste is not just smart business, it’s vital for the planet. We hope that our technology directly contributes to cutting greenhouse gas emissions and building a sustainable future,” Mc Donnell concludes.
