The vision engine

One engine that reads the photo, weighs the evidence, and explains the call.

Every Agrofuze capability runs on the same core: capture an image, analyze it for the signatures of disease, pests and deficiency, score its health, and suggest a next step. Here is how each stage works, and where each capability fits.

Early blight
Leaf spot
Lesion
Scanning Tomato leafConfidence 89%
0%
Health ScoreAt risk
The four-stage flow
1
Capture
A phone photo of a leaf, plant or field section.
2
Analyze
Symptoms located and classified across disease, pest and nutrient models.
3
Score
Health score plus confidence, so borderline reads stay honest.
4
Recommend
A plain-language next step for the top-detected issue.
A note on honesty

A reading you can trust is one that admits what it does not know

Agrofuze never hides uncertainty behind a confident label. Confidence travels with every finding, coverage limits are stated on each capability page, and treatment output is always framed for review.

  • Confidence shown on every detection, not just the strong ones.
  • Coverage and accuracy caveats stated plainly, per capability.
  • Treatment output positioned as a suggestion to review, never an automatic prescription.
  • The same scan motion appears across the product, so what you see here is what you get in the field.
Upload a leaf photo, or drag it here
No photo? Try a sample:
Live detection

Upload a leaf photo.
See what Agrofuze finds.

This is exactly what a farmer sees in the field, in seconds - the scan sweeps the image, marks what it detects, and returns a health score with the reasoning behind each finding.

1Run the scan to reveal the diagnosis panel.

Sample output shown for demonstration. Real scans run on your own photos after sign up.