This is like putting a smart security camera in a tomato greenhouse that doesn’t watch for thieves, but constantly watches plants for early signs of disease and automatically counts how many tomatoes are growing.
Traditional crop scouting is slow, manual, and often misses disease outbreaks until it’s too late; yield estimates are also rough and labor-intensive. This system automates high-speed disease detection and fruit counting so growers can react earlier, reduce losses, and plan harvests more accurately.
Domain-specific computer-vision models, labeled plant/disease imagery, and integration into greenhouse monitoring workflows create a data and workflow moat that is hard to replicate quickly.
Open Source (Llama/Mistral)
Unknown
High (Custom Models/Infra)
Real-time high-resolution image processing at scale (compute and bandwidth constraints in large greenhouses).
Early Adopters
Focuses on high-speed, continuous surveillance specifically for tomato crops, combining both disease detection and automated fruit counting in one integrated system rather than separate tools.