Speed of detection
Disease spreads, so it needs to be spotted early.
AI Crop Disease Detection & Recommendation
We built real-time tomato disease detection from images, video and live feeds, paired with fertiliser recommendations so growers know what action to take.

What stood in the way.
Growers need disease detected quickly from images or video, and actionable treatment guidance once it is found.
Disease spreads, so it needs to be spotted early.
Growers may have photos, recorded video or a live camera feed.
Detection is only useful if it comes with guidance on treatment.
How we answered it.
We built real-time disease detection that works on images, video and live feeds, using YOLOv8 and OpenCV, with fertiliser recommendations presented through a Streamlit interface.
The parts that made the difference.
Disease is detected in still images of plants.
The system detects disease in recorded video and live feeds in real-time.
Each detection comes with a fertiliser recommendation.
A Streamlit app gives growers a simple way to use the model.
What changed for the client.
Growers get automated disease recognition with practical next steps.
What it was built with.
Part of our AI and machine learning work.
The next big thing starts with a conversation.
An idea, a challenge, a “what if”. Tell us what you have in mind, and we’ll figure out the next step together.
What happens next
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