Adoption tackled from design

A deep-science agtech company had built precise scientific models that could help verify farmer practices to power sustainability-program enrollment and carbon payments. However, the program enrollment needed the farmer to input their season data first. This exercise was still being done manually and it was time-consuming for both: the client’s program manager and the farmers, including several rounds of back-and-forth between both. On top of that, the Client was facing a hard launch deadline tied to real grower enrollment, payment cycles and seasonality.

Magoya’s embedded team started with a short discovery to understand who the platform had to serve: the farmer, the sustainability program manager and the client’s own enterprise stakeholders. It also defined the data points needed for program enrollment and verification.

With that clear, Magoya built the data infrastructure and the product interface with one objective: take work off each user, not add to it.

At the end of the process, farmers enroll and prove their practices in a few guided steps, program managers see verified, audit-ready data in one place, and everything runs on the client’s own infrastructure. Adoption followed from that framing. Farmers stay focused on the field instead of becoming digital experts; the client receives trusted data it can act on without any collection effort of its own.