The AI-ready infrastructure for agricultural data — unify satellite, soil, FMS, and weather data into one clean, normalized, AI-ready layer.
Precision agriculture depends on high-quality data, but most teams still spend months connecting, cleaning, and translating fragmented agricultural systems before they can build real product value.
3–6 months just to connect a single satellite + FMS source
Every system (FieldView, xFarm, CLAAS, Cropwise) uses different data models
OEM platforms trap customers inside closed ecosystems
Requires deep expertise: cloud masking, atmospheric correction, archive handling
AgriCore is a vendor-neutral agricultural data platform that connects fragmented farm data sources and turns them into one normalized, AI-ready context layer.
It helps teams move from raw, inconsistent data to usable agricultural intelligence — without rebuilding the same integrations again and again.
AgriCore normalizes European agricultural data into a single, clean output that can be used by analytics products, AI models, internal tools, and decision-support systems.
Connect all farm management systems via one API.
Preprocessed imagery — no need for raw data handling.
Unified soil data aligned with fields and operations.
Field-level forecasts and historical insights.
Every data source flowing through AgriCore follows the same four-stage normalization pipeline.
The ENUC Pattern — Four Layers, One Output.
Pull raw data from FMS APIs, satellite feeds, soil databases, and weather endpoints.
Map proprietary schemas to AgriCore's unified field/boundary/activity data model.
Entity resolution engine matches fields across sources — one canonical record per field.
Apply crop season logic, regional calibration, and agronomic units before output.
When a trading house has growers reporting through John Deere, CLAAS Connect, and Climate FieldView, one field shows up three times under three names. Agricore's engine matches, deduplicates, and creates a single canonical field record across all sources using geospatial overlap analysis — so years of normalized, entity-resolved history line up in one place. This is where the data becomes actionable.
Built for European Agricultural Innovators
Multi-tenant access control, GDPR-compliant data handling, and field portfolio management across hundreds of farms.
Skip 3–6 months of integration work. Connect your AI model or analytics product directly to normalized, AI-ready field data.
Supply chain risk intelligence, crop monitoring, and normalized field data for pricing and underwriting models.
Manage multi-farm portfolios with unified data across all your clients' FMS platforms and satellite sources.
Everything you need to know about Agricore