System
Algorithmic Cultivation
A seasonal feedback loop that blends ranch craft with AI assisted pattern recognition.
Seasonal Feedback Loop
ALGX runs on a seasonal feedback loop. Each run becomes part of a long-term dataset that helps us refine decisions, timing and consistency season after season.
We focus on real-world variables that actually matter: soil inputs, organic amendments, feed volume, humidity, yield performance, terpene expression and visual plant health. Each season is recorded, compared and folded into the next.
Outdoor & Mixed Light Environment
Layered Living Soil Beds
Season Based Data Logging
AI Assisted Pattern Recognition
Manual Control, Informed by Data
What the Model Actually Does
The model doesn't automate the ranch. It studies historical runs and reveals patterns in how certain decisions influence outcomes. It sharpens intuition - it doesn't replace it.
Over multiple seasons, that means more confidence in how a cultivar will express itself in our beds and under our conditions.
Human First, Data Supported
Field notes, real-weather behavior and hands-on experience are treated as real data points and folded back into the system.
The result is cleaner, more dependable flower, season after season.