Caatinga Rover also needs to organize data, routes and decisions
Software for a better farm shouldn't just be a nice-looking screen. It needs to help turn real work into records, planning and operational learning.
Caatinga Rover was born as a robotic base for physical tasks, but its evolution includes an application layer to support farm management, activity planning and validation reports. This digital layer is under development and follows the project's TRL 5 stage.
From physical operation to farm management
The pages below separate different producer needs and connect each one to a possible function of the digital layer.
Farm management
Organize tasks, history, worked areas and data collected by the robot into a useful view for the property.
Go to farm management → 02Agricultural planning
Plan routines, prioritize areas, prepare missions and reduce improvisation before putting the rover in the field.
Go to agricultural planning → 03Agricultural consulting
Turn records, images and telemetry into evidence for technical conversations and agronomic decisions.
Go to agricultural consulting →Not "just another generic record-keeping system"
Caatinga Robotics' difference lies in the link between the physical operation and the data born in the field. A recorded route, a collected image, a mowing task or a spraying trial can become history, comparison and a report.
This view is complementary to traditional rural software. The initial focus is to support validation, demonstrations, test areas and decision-making with verifiable information.
How the application connects to Caatinga Rover
The sequence below shows the public view of the flow. Internal engineering, code and calibration details remain confidential.
- 1Plan
Define area, task, crop, constraints and operation objective.
- 2Execute
Drive manually or validate assisted routes under supervision.
- 3Record
Associate route, event, image and operational data with the area's context.
- 4Analyze
Generate history and support technical reports, without any guaranteed-performance promise.
The configurator's simulator is already the first piece of this digital layer
Before any complete management system, the Caatinga Rover configurator already calculates, today, a real "Scenario hypothesis": you enter soil type, vegetation density, terrain condition and approximate area, and get hectares per hour, estimated autonomy and days needed for the informed area.
This isn't a future promise — it's the same physics engineering behind what this hub describes as a vision, already running in production. The difference between the configurator and the "software for a better farm" described here is the horizon: one calculates a hypothesis before the operation; the other, still under development, would record what actually happened afterward.
About Caatinga Rover's digital layer
Is the digital layer already available?
Not as a complete system. The configurator already calculates scenario hypotheses today; historical records, formal planning and consulting reports remain under development, following the project's TRL 5 stage.
Does this software replace a farm ERP or technical consulting?
No. The proposal is complementary: organizing data born from the robot's operation, not replacing complete management systems, agronomists or qualified technicians.
What data does the digital layer intend to organize?
Worked area, task performed, implement used, route traveled, images and field events — the same soil, vegetation and terrain vocabulary the configurator already uses to calculate the scenario hypothesis.
Where this fits in the Caatinga ecosystem
The robotic base that performs physical tasks and provides operational data.
Learn about the rover → ImplementsMower, sprayer and modules under development connected to real tasks.
See implements → Field validationCriteria for turning trials into auditable technical evidence.
See validation → Talk to the teamPresent your area, crop and repetitive task for an initial analysis.
Get in touch →Want to test management, planning and field work in the same flow?
Tell us the repetitive task, the crop, the area and the type of record you'd like to track.