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Vivid Machines raises $5.8 million CAD to help growers virtually monitor fruit trees

Toronto-based agtech startup Vivid Machines, which provides monitoring technologies for the fruit supply chain, has raised $5.8 million CAD ($4.3 million USD) in seed funding.

Founded in 2020 by Jenny Lemieux (CEO) and Jonathan Binas (CTO), Vivid Machines has developed a vision system that uses spectral sensors to help growers, packing facilities, and fruit marketers capture data for permanent crops.

The funding will help Vivid Machines expand to a wider variety of crops.

Crops that tend to grow uniformly like corn can be monitored in bulk using drone or satellite technologies. Permanent crops, such as apples and peaches, are usually trees or shrubs. With the canopy of leaves from the trees covering their fruit, the same overhead monitoring technologies are not ideal for permanent crops. To get around this, Vivid Machines’ technology uses imaging and AI to capture chemical and physical profiles of permanent crops.

According to Vivid Machines, using its platform can help growers manage their crop’s progress and predict yields by providing accurate real-time crop data, down to the individual plant.

Vivid Machines said the funding will support the startup in its development of a “broader set of system applications” and expand its capabilities to a wider variety of fruit crops.

The round was led by BDC Capital’s Thrive Venture Fund, with participation from StandUp Ventures, Algoma Orchards, Tall Grass Ventures, Entrepreneur First, BoxOne Ventures, Conexus Venture Capital (Emmertech), the W Fund, Cornell Capital, Freycinet Ventures, N49P, and MaRS IAF.

RELATED: Four startups from initial Entrepreneur First Toronto cohort raise collective $5.7 million CAD

In January, Vivid Machines was awarded more than $810,000 from the federally supported Canadian Food Innovation Network for its project with Ontario-based farms Algoma Orchards and Blue Mountain Fruit Company, which both specialize in apples. Under the partnership, Vivid Machines is creating digital twins, or virtual models, of the orchards to determine ideal harvest timings to meet the demands of grocers and food processors.

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