Survey
A manually piloted drone captures high-resolution crop imagery across the field.
See disease sooner.
Treat only what matters.
ARIX is building an AI-powered crop intelligence system that surveys wheat fields, detects disease, and maps exactly where attention is needed.
StageConcept + prototype development
Initial cropWheat
First deploymentPrivate field trials
01 / Mission
Every field tells a story.
ARIX makes it visible.
Uniform spraying treats every acre the same. We are building a more precise path: find affected zones, understand disease pressure, and support treatment decisions with field-level intelligence.
02 / Company momentum
Progress, made visible.
Live totals from posted ARIX finance records. Individual transactions and employee data remain private.
Live ledgerPKR · Posted records only
100%of visible capital
Earned value
Revenue generated through ARIX activity.
Rs 100,000 of Rs 100,000 in combined public financial momentum.
Combined financial momentumRs 0
03 / System
From crop to coordinates
A practical first MVP that proves the intelligence pipeline before adding flight autonomy.
Detect
A laptop-based AI pipeline identifies healthy wheat and priority disease classes.
Map
Imagery and flight logs are synchronized into a geo-referenced disease heat map.
Act
The grower receives a clear report that turns crop signals into focused field decisions.
04 / Intelligence layer
Signals you can act on.
ARIX is initially focused on four wheat conditions. Explore the interface concept to see how field imagery becomes a readable disease map.
Inside the technology →ARIX / FIELD 01 MODEL PREVIEW
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Detected classYellow rust
Model confidence91.8%
05 / Intended impact
Precision with a purpose
These figures are product targets from the current implementation plan. Field validation is still ahead.
20–40%
Target chemical reduction
By focusing future treatment on mapped disease zones rather than the entire field.
01
Lower input waste
Support more intentional use of crop protection products.
02
Faster scouting
Turn aerial coverage into a field report that is easier to review.
03
Decision history
Build a data layer for comparing disease patterns over time.
06 / The path forward
Prove the intelligence.
Then automate the response.
MVP-A validates manual survey, post-flight detection, geo-referencing, heat maps, and reporting. MVP-B introduces waypoint autonomy and onboard processing.
View the roadmap →Build the future of field intelligence