The problem is bigger than it looks. We have seen it from the inside.
Why the most expensive decisions in horticulture are still made by gut feel, and what we are doing about it.
Every season, growers bet everything on decisions they cannot fully see.
A grower managing 50 acres of apple trees makes one chemical thinning decision per season. Spray too much, too little, or a day late, and the margin is gone. That call is still made by walking rows, reading clouds, and hoping the timing is right.
Labour compounds it. The most profitable growers spend roughly a third of income on labour. The least profitable spend over half. Every re-walk, missed spray window, and unplanned crew hour is a cost that didn't need to exist.
This is not a niche inefficiency. It is the central operational problem of commercial horticulture, and it has remained unsolved not for lack of science, but for lack of someone willing to carry that science all the way to the field.
That is what we are building. Starting with the highest-stakes decision in the orchard calendar, and expanding from there.
Our approach.
Not a dashboard. Not another sensor. A system that deploys computer vision hardware into orchards to replace the guesswork in apple thinning with specific, data-driven spray recommendation — timing, dosage, and scheduling — derived from each grower's own trees.
Targeted decision spraying
Less herbicide, lower input costs
A smaller footprint on the land
We did not stumble into this problem. We come from research and engineering backgrounds that sit at the exact intersection of what this industry needs. The science has existed for decades. What it needed was someone willing to carry it all the way to the field.
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