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Artificial IntelligenceDeliveredCrop health analytics

Crop health analytics — Horticulture

Satellite and drone imagery models for yield, stress and disease. Delivered for a horticulture client in Visakhapatnam.

Location
Visakhapatnam
Year
2026
Duration
21 weeks
Team
8 engineers
Interactive 3D · drag to rotate
21%
yield uplift
54k
hectares
21k
farmers

The challenge

Existing vendors had delivered pieces of a crop health analytics system, but nobody owned the integration and the pilot had stalled.

What we built

A phased rollout: a measured pilot first, then scale-out. The core runs on PyTorch with GDAL, integrated into existing systems through Flutter.

Delivery timeline

  1. Phase 1

    Discovery sprint and site survey

  2. Phase 2

    Prototype built and tested in the Motera lab

  3. Phase 3

    Pilot on site with before/after measurement

  4. Phase 4

    Scale-out, training and handover

Highlights

  • Operator training delivered in Gujarati, Hindi and English
  • Runs on-premises; no data leaves the site unless agreed
  • Documentation, drawings and source handed over at close
  • Safety case reviewed with the client's EHS team

Have a problem that needs a machine built for it?

Tell us the constraint — line speed, accuracy, environment, deadline. An engineer will read it and reply with a straight answer, including when the answer is that you don't need us.

We reply to every enquiry within one business day.