Agriculture & Agtech

Farming became a data problem with a very short window to act.

Our goal in this sector

Make agronomic and operational data usable by the people in the field.

// 01 — State of Play

Where the
sector stands.

Modern operations generate soil, weather, imagery, equipment, and yield data continuously. Most of it lands in vendor silos tied to whoever sold the hardware, which means the grower cannot see it together and cannot act on it inside the narrow window where a decision still matters.

Downstream, buyers increasingly demand traceability and sustainability documentation. That turns record-keeping from a compliance chore into a commercial requirement — and into a systems problem, because the records start in a tractor cab.

// 02 — The Shifts

What technology is changing right now.

The forces reshaping this industry — and why they turn into engineering problems.

Shift 01

Equipment became a data source

Machinery telemetry reports position, rate, and yield in real time, enabling as-applied verification instead of estimates.

Shift 02

Imagery got cheap and frequent

Satellite and drone imagery at short revisit intervals supports in-season intervention rather than post-season analysis.

Shift 03

Traceability moved up the chain

Processors and retailers want field-level provenance, which requires records that survive from planting to delivery.

Shift 04

Inputs got prescriptive

Variable-rate application ties agronomic models to machine control, which raises the stakes on data quality.

// 03 — Friction

Where it breaks today

  • Field data locked in three vendor portals that do not export cleanly
  • Paper spray and harvest records reconciled at season end
  • Equipment downtime discovered when a crew arrives at the field
  • Contract and delivery tracking done in a notebook
  • No usable history when a buyer asks for provenance
// 04 — What We Build

Systems that fix it

Unified farm data layers

One store for boundaries, operations, imagery, and yield across mixed equipment brands and vendor platforms.

Field and crew mobile tools

Offline capture of scouting, applications, and harvest activity, tied to the field boundary and the operator.

Traceability and compliance records

Chain-of-custody from field to load to delivery, exportable in the format your buyer actually requires.

Contract and logistics tracking

Grain or produce contracts, deliveries, settlements, and basis tracked against actual movement.

// 05 — Ground Rules

How we engineer here

Connectivity

Rural coverage is unreliable. Everything field-facing is offline-first with deferred sync.

Equipment standards

ISOBUS and vendor APIs vary widely; ingestion has to be tolerant and normalize aggressively.

Seasonality

Systems are idle for months then hit hard for weeks. Capacity and support planning follow the calendar.

Data ownership

Growers own their agronomic data. Terms and export rights must be explicit.

// 06 — Glossary

The language of the sector

Plain-English definitions, so nobody has to pretend they know what an acronym means.

Variable rate
Applying inputs at different rates across a field based on a prescription map.
As-applied
The record of what was actually applied, as reported by the machine, versus what was planned.
NDVI
A vegetation index derived from imagery, used as a proxy for crop vigor.
Basis
The difference between local cash price and the futures price for a commodity.
ISOBUS
The equipment communication standard that lets implements and tractors exchange data.
// 07 — Questions

Straight answers.

Can you pull data from mixed equipment brands?

Yes. Normalizing across brands and vendor portals is usually the first thing we build.

Does it work without signal in the field?

Yes — offline capture and sync is standard for anything used in the field.

Can you produce buyer traceability reports?

Yes, in whatever format the buyer or certifying body requires.

Running one of these
operations?

Describe your setup to our AI Strategist and get an architecture sketch back in seconds — or go straight to a human.