From farm plots to global supply chains — monitor, verify, and report with confidence. Streamline EUDR compliance through scalable, API-ready geospatial intelligence.
Most companies affected by the EU Deforestation Regulation don’t have a policy problem — they have a data problem. Farm plots that were mapped once and never updated. Supplier geolocation data that’s incomplete, inconsistent, or arrives in a dozen different formats. Due diligence workflows that don’t scale past a few hundred plots.
The regulation’s timeline has shifted, but the underlying due diligence obligations haven’t.
EUDR applies from 30 December 2026 for medium and large operators and traders, and from 30 June 2027 for micro and small operators.
The regulation covers cattle, cocoa, coffee, oil palm, rubber, soy, and wood, including selected derived products.
For in-scope operators, due diligence includes plot-level geolocation, deforestation risk assessment, and traceability back to the production plot.
Picterra turns fragmented supplier data into a verified, audit-ready picture of deforestation risk across your entire supply chain — at the plot level, at scale.
Ensure precision and reliability of your supply chain data with a rigorous data quality assessment process.
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Simplify the complexity of obtaining accurate geolocation data for your supply chain through seamless collaboration with suppliers.
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Apply advanced geospatial AI to assess deforestation risks in your supply chain & complement existing deforestation resources.
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Facilitate data analysis auditing through transparent documentation, ensuring compliance and accountability.
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Easily scale, customize, and automate periodic risk assessment reporting.
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Streamline the process of submitting compliance data to the TRACES system for regulatory approval.
Ensure precision and reliability of your supply chain data with a rigorous data quality assessment process.
Learn more
Simplify the complexity of obtaining accurate geolocation data for your supply chain through seamless collaboration with suppliers.
Learn more
Apply advanced geospatial AI to assess deforestation risks in your supply chain & complement existing deforestation resources.
Learn more
Facilitate data analysis auditing through transparent documentation, ensuring compliance and accountability.
Learn more
Easily scale, customize, and automate periodic risk assessment reporting.
Learn more
Streamline the process of submitting compliance data to the TRACES system for regulatory approval.
Picterra verifies production plots for deforestation risk, enabling transparent, auditable due diligence and providing the evidence required for EUDR compliance. Powered by Picterra Tracer, the solution automates risk assessments through advanced data ingestion and analysis, delivering clear insights for regulatory reporting. Flexible APIs and modular workflows integrate seamlessly with existing traceability and supply chain systems while maintaining high data quality.
Obtaining accurate geolocation data for supply chain elements like farm plots, mills, and processing locations is often challenging—frequently incomplete, outdated, or fragmented across multiple partners. Picterra helps address these challenges by digitalizing sourcing parcels, intermediate storage sites, and processing facilities, while performing robust data quality verification. This enables the creation of a complete, accurate digital footprint of your supply chain, ensuring data corrections and enhanced reliability throughout your entire network.
The verification of geolocation data (GPS points and polygons) is a critical step in ensuring the precision and reliability of spatial data for due diligence. Each data point undergoes rigorous quality assessment and compliance checks. Our methodology applies 30+ calibrated stress tests, assigning a score to each farm record and categorizing results by risk level (low, medium, high). As suppliers update the database, Picterra verifies, cleans, and maintains records to uphold consistently high data quality.
We leverage advanced geospatial AI technology to review and analyze your digitalized sourcing locations against approved deforestation maps. Where necessary, we complement the data with high-temporal and spatial deforestation information. The goal? Drawing insights into the deforestation status of your analyzed sourcing parcels, meeting the requirements of the EUDR regulation.
The outcome is a detailed and comprehensive risk assessment report based on the analysis, with the option to subscribe to automated, periodic assessment reports. Additionally, Picterra Tracer ensures that this report is aligned with EUDR requirements, streamlining submission to the TRACES system. It also includes a Due Diligence Statements (DDS) report, consolidating your deforestation risk data. This approach ensures continual compliance and monitoring, keeping your supply chain aligned with the ever-evolving landscape of regulations and sustainability standards.
Walter Matter, a century-old, family-owned merchant specialized in coffee and cocoa trading, needed reliable traceability across a global network of smallholder suppliers. With Picterra, their lean team uploads farm data in any format, runs satellite-based deforestation risk assessments, and generates transparent, auditable reports, all without GIS expertise or added operational complexity.
analyzed across 26 countries
managed
verified
Sustainability Manager at Walter Matter SA
With EUDR deadlines looming, Facta International turned to Picterra to build a scalable, transparent verification workflow. By analyzing up to 150,000 plots, they now assess geolocation accuracy, deforestation risk, and supplier data quality in one unified system. This enables traceability and compliance across diverse sourcing regions.
across 11 origin countries
by classified plots by deforestation risk
Trader at Facta International
Businesses face challenges with the EU Deforestation Regulation (EUDR). Picterra aids compliance with its geospatial AI platform, offering verified supplier data, advanced risk assessments, and dynamic deforestation monitoring.
