Enabling smart farming with high-quality training data to accelerate ML model development and deliver precise, real-time decisions.

Use cases

Precision Soil Health Analysis
Identify missing nutrients with precision chemical soil analysis and AI-driven data annotation. Boost crop yield and maintain soil health effortlessly.

Smart Crop Protection with Data Annotation
Harness data annotation for real-time crop monitoring, disease forecasting, and precision pest control. Protect your fields with smart, AI-driven crop protection for higher yields.

AI-Powered Crop Quality Control
Leverage AI-powered data annotation to monitor crop ripeness, size, and color. Accurately forecast harvest time and automate quality control for higher yield and consistent produce.

Smart Livestock Tracking
Ensure accurate livestock monitoring and error-free animal counts across multiple locations with advanced annotation technology.

Smart Weed Detection for Chemical-Free Farming
Boost crop health with AI-powered weed monitoring that automatically identifies unwanted plants, reduces chemical usage, and promotes sustainable agriculture.

Smart Crop Nutrition with Data Annotation
Use data annotation to improve crop nutrition—time irrigation accurately, apply nutrients effectively, and predict the right agronomic mix to boost yields and reduce waste.
Learning Spiral AI for Smart Agriculture
Empowering modern farming with AI-ready, human-annotated datasets. Learning Spiral AI delivers high-quality data for crop monitoring, weed detection, livestock management, and yield prediction.
Our scalable workflows and strict quality checks help agri-tech innovators build reliable computer vision models that boost efficiency and drive sustainable agriculture.


