The age of autonomous farming has begun

Cropion brings autonomous intelligence to your fields — deploy smart rovers in minutes, gather real-time insights, and farm with precision like never before.

🇮🇳 Built for Indian fields, with Indian farmers. We're prototyping and learning every day — your feedback matters.

Key Features

Building for every farm — from fields of today to farms of the future

Comprehensive AI-powered farming solutions that transform traditional agriculture into smart, sustainable, and profitable operations.

AI Weed Detection

Advanced computer vision technology identifies and targets weeds with 99.5% accuracy, reducing herbicide usage by up to 70% while protecting your crops.

Crop Monitoring

Real-time health monitoring tracks growth patterns, nutrient levels, and disease indicators to optimize yield and prevent crop loss.

Autonomous Rovers

Self-navigating rovers work 24/7 across your fields, performing precise interventions and data collection without human supervision.

Yield Analytics

Predictive analytics forecast harvest yields, optimize planting schedules, and identify opportunities for productivity improvements.

Sustainability Tracking

Monitor environmental impact, track carbon footprint, and optimize resource usage for sustainable farming practices.

Precision Agriculture

GPS-guided precision application of fertilizers and treatments ensures optimal resource utilization and minimal environmental impact.

How it works

Building the Future, Step by Step

Our R&D journey is focused on iterating, testing, and learning from the field as we develop full autonomy for farming.

Deployment Process

Complete setup in 4 comprehensive steps

Initial Field Study

Exploring real-world conditions and identifying R&D challenges

Select test plots with diverse terrain and crop types

Gather environmental and soil data to inform design

Identify logistical and practical deployment issues

Map early risks and edge cases in the field

Prototype Testing

Testing early rover builds under real conditions

Deploy initial prototypes to test mobility and safety

Evaluate hardware performance in live terrain

Manually log operational issues and breakdowns

Refine mechanics and electronics based on observations

Sensor Integration

Experimenting with sensory inputs and data capture logic

Test soil, proximity, and visual sensors for responsiveness

Validate data quality and environmental noise resistance

Integrate with onboard processing units

Iterate firmware for stability and accuracy

Autonomy Trials

Early tests for navigation, task execution, and error handling

Implement basic autonomous routines (e.g., straight path driving)

Simulate obstacle detection and avoidance

Manually validate weeding or crop interaction modules

Document AI feedback loops and training needs

Initial Field Study

Exploring real-world conditions and identifying R&D challenges

Select test plots with diverse terrain and crop types

Gather environmental and soil data to inform design

Identify logistical and practical deployment issues

Map early risks and edge cases in the field

Prototype Testing

Testing early rover builds under real conditions

Deploy initial prototypes to test mobility and safety

Evaluate hardware performance in live terrain

Manually log operational issues and breakdowns

Refine mechanics and electronics based on observations

Sensor Integration

Experimenting with sensory inputs and data capture logic

Test soil, proximity, and visual sensors for responsiveness

Validate data quality and environmental noise resistance

Integrate with onboard processing units

Iterate firmware for stability and accuracy

Autonomy Trials

Early tests for navigation, task execution, and error handling

Implement basic autonomous routines (e.g., straight path driving)

Simulate obstacle detection and avoidance

Manually validate weeding or crop interaction modules

Document AI feedback loops and training needs

Initial Field Study

Exploring real-world conditions and identifying R&D challenges

Select test plots with diverse terrain and crop types

Gather environmental and soil data to inform design

Identify logistical and practical deployment issues

Map early risks and edge cases in the field

Prototype Testing

Testing early rover builds under real conditions

Deploy initial prototypes to test mobility and safety

Evaluate hardware performance in live terrain

Manually log operational issues and breakdowns

Refine mechanics and electronics based on observations

Sensor Integration

Experimenting with sensory inputs and data capture logic

Test soil, proximity, and visual sensors for responsiveness

Validate data quality and environmental noise resistance

Integrate with onboard processing units

Iterate firmware for stability and accuracy

Autonomy Trials

Early tests for navigation, task execution, and error handling

Implement basic autonomous routines (e.g., straight path driving)

Simulate obstacle detection and avoidance

Manually validate weeding or crop interaction modules

Document AI feedback loops and training needs

Join us in shaping the future

We’re in active development — collaborate, test, or give feedback on the next generation of agri-autonomy.

Currently in field testing – insights evolving every day