On a modern fruit farm, the most critical data is fleeting. To capture it, a grower has traditionally had two bad options: walk the rows with a clipboard, or fly a drone over and wait hours for processed imagery. Vivid Machines offers a third. Its Vivid XV3 camera system is a black box designed to be bolted onto the sprayer arm or cab of a tractor, capturing a continuous stream of images as the machine moves through the orchard on its normal work. The promise is not just vision, but vision without an extra pass.
Founded in Toronto in 2020, Vivid Machines is betting that the future of precision agriculture is not in adding new, dedicated hardware, but in making the hardware that's already there see. The company, led by co-founders Jenny Lemieux and Jonathan Binas, has raised an undisclosed seed round totaling approximately $4.3 million from a consortium of agtech and venture funds [Business Wire, 2023].
The hardware wedge
The Vivid XV system is the company's core physical intervention. It is a ruggedized, AI-powered computer vision camera that growers are instructed to mount on existing equipment. By avoiding the need for a separate, dedicated scouting vehicle or drone flight, Vivid Machines reduces the operational friction and cost of adoption. The software then processes the visual stream to deliver crop load management insights [Vivid Machines blog, 2025].
A founder built for the field
The company's leadership carries a specific blend of credentials. CEO Jenny Lemieux holds graduate degrees in product and AI management and led AI product teams at Walmart and Ford [Vivid Machines about page]. CTO Jonathan Binas was a postdoctoral fellow at Mila, the Quebec AI Institute, and collaborated with renowned AI researcher Yoshua Bengio [The Org, 2026].
| Founder | Role | Key Background |
|---|---|---|
| Jenny Lemieux | Co-Founder & CEO | AI product leadership (Walmart, Ford); farm upbringing; Masters in Product & AI Management [Vivid Machines about page]. |
| Jonathan Binas | Co-Founder & CTO | Postdoctoral Fellow at Mila (Quebec AI Institute); PhD from ETH Zürich; collaboration with Yoshua Bengio [The Org, 2026]. |
The crowded field of agtech vision
Vivid Machines is entering a sector where computer vision is no longer novel. The company's differentiation rests on three claims: real-time processing, per-plant resolution, and the hardware-mounting strategy that avoids extra passes. The risks for Vivid Machines are the daily realities of selling hardware-software systems into agriculture: sales cycle length, data skepticism, and technical robustness in harsh environments.
The next growing season
With a seed round closed and a team estimated at around 19 employees [PitchBook, 2026], Vivid Machines is likely in a phase of proving its model on commercial farms. The next twelve months will be about moving from undisclosed pilots to named flagship customers. Key milestones to watch include a potential Series A round, the announcement of partnerships with major equipment manufacturers, and the publication of detailed yield improvement and labor savings data from real growers.