Rows of leafy greens growing under LED lights in a vertical farm
Grow intelligence platform

One layer that sees, senses, advises and acts on every zone.

Cropmotive brings vision diagnostics, environment sensing, nutrition guidance and equipment automation together — catching problems days before they show and turning grow data into action across the whole facility.

Live
6 zones · 3 cameras

Command center

Z-01Healthy

Butterhead

96

Z-02Healthy

Basil

94

Z-03Watch

Romaine

71

Z-04Healthy

Kale

98

Z-05Healthy

Arugula

91

Z-06Healthy

Mint

95

Z-03 · nitrogen trend predicted to show symptoms in ~4 days

24/7

Continuous zone scoring

~4 days

Typical early warning window

0

New cameras required

1 week

Typical time to go live

One platform, four layers

Not a camera app — a complete grow intelligence system.

Vision is only one input. Real control comes from combining what you see with what you measure, what to feed and the equipment that carries it out.

The closed loop

Sense, diagnose, advise, act, confirm.

Each layer feeds the next, so an issue is found, corrected and verified — usually before anyone walks the floor.

  1. 01

    Sense

    EC drifting low in Zone 03

  2. 02

    Diagnose

    Nitrogen uptake risk building

  3. 03

    Advise

    Raise N by 12%, dose A+B

  4. 04

    Act

    Doser applies the correction

  5. 05

    Confirm

    EC recovered, health climbing

Detection to prediction

Not just what is wrong today — what is coming this week.

By combining imagery, sensor trends and feeding history, Cropmotive projects where a zone is heading, so you intervene before yield is lost rather than after.

See predictive intelligence

Day 1 · Zone Z-03 · Romaine

Healthy · 94

Leaf colour, growth rate and sensor readings all in range. No visible symptoms.

Day 4 · Zone Z-03 · Romaine

Watch · 71

Nitrogen deficiency pattern forecast to become visible within four days. Suggested action: raise N for Z-03 and re-check in 24 hours — auto-dosing available.

Grow-cycle learning

Learn what actually worked, cycle over cycle.

Each harvest becomes evidence, so the next cycle starts from what your own operation already proved works best.

Cycle comparison · Romaine · Rack B

Cycle 11

92%

yield vs. plan

EC held steady; no deficiency events

Cycle 12

84%

yield vs. plan

Late N dip caught, partial recovery

Cycle 13

96%

yield vs. plan

Feed adjusted from cycle 12 learning

See grow-cycle & yield analytics
A grower photographing basil plants with a phone in a vertical farm

Mobile app & field intelligence

The same intelligence, in the hand of the person on the floor.

Capture a zone, read its score, follow the recommended correction and log the work — offline in the middle of the room, synced the moment you have signal.

Explore the mobile app

Built for real facilities

Made for controlled-environment growers.

Why one connected layer beats point tools

Shared context

The prediction model sees the same history the dashboard shows and the reports export — no data silos between features.

Improves with use

Diagnostics and forecasts sharpen on your own accumulating camera and outcome data, cycle over cycle.

Advisory or autonomous

Run it as a recommendation engine, or let it act on connected pumps, dosers and fans within limits you define — your call, per zone.

Stop reacting to your crop. Start running it with intelligence.

See Cropmotive running on your own zones — cameras, sensors, feeding and equipment, working as one.