AI Built for Saudi Agriculture
LYMTA builds AI systems that solve real problems across the Saudi agricultural value chain. From harvest timing to pest detection to precision spraying to post-harvest grading. Four engines, one platform architecture, ready to deploy.
What AI Makes Possible
Four production-grade computer vision systems for farms, orchards, and processing lines. Profile-driven, edge-first, bilingual. Designed from the ground up for Saudi operations.
The Status Quo
Harvest timing relies on visual guesswork. Pest detection depends on manual field walks across thousands of trees. Herbicide is applied uniformly whether weeds are present or not. Post-harvest grading varies shift to shift because it depends on inspector judgment, not data.
What LYMTA Has Built
Production-ready. Deployable in 6 to 8 weeks.
Crop Ripeness Engine classifies harvest readiness from smartphone, drone, or tractor camera images. Palm Guard detects Red Palm Weevil from drone imagery with per-tree GPS coordinates and severity scoring. See and Spray mounts on tractor booms and fires nozzles only over detected weeds in real time. All three share a profile-driven architecture where new crops, varieties, or weed species are YAML configurations, not code changes.
- • Three engines, one architecture: ripeness, pest detection, precision spraying
- • Profile-driven: new crops and varieties via YAML, no engineering needed
- • 398 automated tests across the three field engines
The system classifies produce by grade, calculates batch composition percentages, and estimates SAR value per batch. One platform handles multiple product lines through configurable grading profiles. Built for packhouses, processing plants, and export-grade quality control where shift-to-shift inspector variance is the core problem.
- • Classifies produce by grade with batch composition and SAR valuation
- • Configurable profiles for dates, stone fruits, vegetables, and more
- • Built for packhouses and export-grade quality control
From First Meeting to Full Deployment
A structured four-step process built around your operations.
We visit the site, understand the workflow, and define a concrete scope with measurable outcomes. For ripeness, identifying target zones. For Palm Guard, mapping plantation blocks. For See and Spray, surveying boom configuration. For grading, auditing current inspection processes.
We collect and label data from your actual operations. Each product means training a custom YOLOv8 model on your specific crop, pest, weed, or product mix. New varieties or grades are delivered as YAML profiles plus trained models, not platform rebuilds.
We install on-site and integrate with your existing systems. All systems run on-premise on edge hardware. Crop Ripeness and Palm Guard run on any laptop or edge device. See and Spray runs real-time on NVIDIA Jetson. Operator training in Arabic and English.
We retrain models as your operations evolve, handle seasonal calibration, tune confidence thresholds based on field performance data, and expand to new crops, varieties, or facilities.
Ready to See This
at Your Operation?
Two-week scoping engagement. We visit your operation, understand the workflow, and return with a fixed-scope pilot proposal tied to one specific product and one specific site.
Contact hello@lymta.aihello@lymta.ai · lymta.ai · Jeddah, Saudi Arabia
Move With Meaning