Turns soil into data, and data into decisions.
An analytics platform with a multi-layer database architecture that optimizes soil-mapping workflows and data-compilation engines for farmland, turning field data into fast, reliable reports.
At its core, Agros is a comprehensive analytics application built to process and analyze agricultural data. It runs on a multi-layer database architecture that optimizes soil-mapping workflows and data-compilation engines for farmland.
Its calculation algorithms were refined with feedback from the field. Thanks to an advanced backend architecture, mountains of data become fast, meaningful reports for farmers and agribusinesses — shortening the path from a lab result to a parcel-level decision.
A database schema that models parcel, depth, and sample layers separately, keeping data from different years on the same plot directly comparable.
Soil productivity indices are computed with formulas calibrated by field feedback, and the result is broken into explainable components rather than a single opaque score.
Lab outputs, field measurements, and morphology records are normalized in a single pipeline; faulty or incomplete samples are flagged and excluded from the report.
Parcel-level, printable reports are generated within seconds from datasets containing thousands of samples.
Moisture and natural-fertility variables were deliberately left out of the index calculation module, so the system focuses only on the most critical agricultural metrics and results stay verifiable in the field.
The multi-layer database architecture is indexed so the compilation engine can process thousands of samples in a single query.
We'll email you the file covering the module list, screen flows, and integration details.
What people ask us, answered briefly and plainly.
An analytics platform with a multi-layer database architecture that optimizes soil-mapping workflows and data-compilation engines for farmland, turning field data into fast, reliable reports.
Multi-layer soil mapping: A database schema that models parcel, depth, and sample layers separately, keeping data from different years on the same plot directly comparable. Refined index calculation: Soil productivity indices are computed with formulas calibrated by field feedback, and the result is broken into explainable components rather than a single opaque score. Data compilation engine: Lab outputs, field measurements, and morphology records are normalized in a single pipeline; faulty or incomplete samples are flagged and excluded from the report. Fast reporting: Parcel-level, printable reports are generated within seconds from datasets containing thousands of samples.
Pricing depends on how many people will use it, which sections are opened, and whether it must connect to other programs. After the conversation we send a written quote with scope, timeline, and a firm price within 48 hours at the latest.
Yes. For one year after delivery, updates, technical support, and server maintenance continue at no extra charge.
Let's begin
How many users, which modules, which integrations — a clear scope and price within 48 hours.
