A farm's data is usually scattered across a notebook, a feed supplier's invoice and a weather app. Vectiq Field puts the whole operation in one platform: assets and herds, crop plans and grazing, activity logs and treasury, IoT sensor streams, computer-vision disease detection, and blockchain traceability for the buyer at the end of the chain. An AI layer of specialised services sits across all of it.
Launch app ↗Track crops, livestock, hives and equipment with ID tags, and capture work in the field on a mobile app that syncs when the signal comes back.
Plan seasons, rotations and grazing blocks against real field boundaries imported from KML, then measure what actually happened against the plan.
Photograph a leaf and get a classification with a confidence figure, backed by a vision service rather than a lookup table of symptoms.
Soil moisture, weather and water-quality readings arrive as data streams, feeding irrigation recommendations and threshold alerts.
A set of specialised services - retrieval, knowledge graph, prediction, recommendation and vision - behind one LLM gateway, so an agronomy question is answered from the farm's own records.
Batch records anchored on a blockchain with smart contracts, so the buyer can verify the history of a lot instead of trusting a printed label.
Accounting, invoices, treasury and quantity tracking share the same records as the operational log, so the harvest figure in the report is the one that was measured.
The surveillance module connects the farm's cameras to the same timeline as everything else, so an intrusion alert sits next to the day's activity log.
Mobile / IoT
Django / PostgreSQL
Vision / RAG / Predict
Crop / Grazing
Blockchain
Accounting / Export
ID tags tie each animal to its own timeline of weight, treatment, grazing block and yield, so a drop in production is traced to an animal and a date rather than argued about.
Seasonal plans are drawn on real field boundaries, work is logged from the field app, disease is caught from a photograph, and irrigation follows soil moisture instead of a fixed timer.
Every batch carries its own history - inputs, treatments, harvest date, handling - anchored on chain, so an export buyer or a retailer verifies the claim instead of taking the producer's word for it.
Smart farm management system integrating AI for crop monitoring, disease detection, and agricultural planning
Season plans drawn on real field boundaries imported from KML, worked from a mobile app that logs offline and syncs when the signal returns
Per-animal records with ID tags, grazing block rotation, treatment history and hive management - knowing which animal, not just how many
Nine specialised services behind one LLM gateway: retrieval, knowledge graph, prediction, recommendation, embeddings and vision for farm data
Accounting, invoices, treasury and yield tracking sharing one record with the operational log - and a batch history the buyer can verify on chain
Cross-platform mobile application for farm management with offline support and camera integration