Nexa Vision
Optical scene acquisition and index computation clipped to each pasture area.
Pasture is the main productive asset and the hardest one to follow closely. Convex monitors areas cycle by cycle with spectral indices, time series and climate context to support grazing management decisions at territorial scale.
In extensive livestock operations, the variable you can observe at scale is pasture, not the animal. Convex monitors grazing areas cycle by cycle with spectral indices, time series and local climate context to support territorial management decisions.

Pasture condition shifts with rainfall and grazing pressure, but is rarely recorded in a comparable way.
Walking every paddock at a useful frequency is not feasible on large properties.
With no historical series, moving a herd depends on a single visual judgement.
Water-deficit periods explain much of a decline in condition, yet stay out of the operational record.
The same architecture runs across every sector. What changes is which layer is critical and which proprietary systems take part.
Optical scene acquisition and index computation clipped to each pasture area.
Reading of cycle-to-cycle evolution and a written territorial diagnosis of the area.
Local climate context applied to the interpretation of the period.
Cycle scheduling and automatic report delivery per area.
Sources compatible with the systems deployed in this sector. No layer is assumed: every monitored area declares what is actually available.
Multispectral scenes validated for cloud cover over the declared area.
Vigour indices computed over each pasture polygon.
GeoJSON polygons per paddock or per group of areas.
Comparison of the same area across cycles and across seasons.
Local rainfall and temperature for the observed interval.
Each application states the problem addressed, the data used, the Convex system involved and the operational output produced.
No objective comparison between paddocks.
Rotation decisions taken without history.
Condition drops with no recorded explanation.
Properties made of many distinct paddocks.
Eligible optical scenes over each pasture area are selected for the cycle.
Indices are computed per polygon, isolating each paddock.
Nexa M1 compares the current cycle against the history of the same area.
Areas with persistent decline in condition are highlighted.
The team decides on rotation, rest or an on-site inspection.
The cycle is archived and feeds the area's time series.
Spatial distribution of pasture condition per area.
Cycle-by-cycle evolution of each monitored paddock.
Written reading of territorial evolution over the period.
One PDF per cycle and per monitored area.
Local conditions matched to the observed interval.
We separate what is in operation from what is still under development. Research and prototypes are never presented as deployed product.
Full per-area cycle with spectral indices and report.
Retroactive comparison across cycles of the same pasture.
Not part of the product. No individual tracking capability is offered today.
Correlating pasture condition with herd performance is under investigation.
Extensive areas under rotational or continuous grazing.
Smaller paddocks that need frequent tracking.
Territorial management of fragmented areas.
Areas that alternate between cropping and pasture through the year.