The Challenge of Verifying Commodity Origins

In today’s regulatory frameworks, proving products origin is no longer optional, it’s operationally and legally essential. But for companies managing thousands of suppliers across fragmented supply chains, verifying the origin of every production area remains a major challenge.

Marvin addresses this challenge by combining geospatial intelligence, advanced AI, and deep land-use expertise.

The Context

Climate change has heightened demands for transparency, especially within the private sector. Sustainability expectations and corporate governance requirements are growing rapidly. At the same time, geopolitical shifts, changing trade policies, and regulations around responsible sourcing, tariffs, sanctions, and deforestation-related restrictions are turning into critical business risks.  According to the UNECE, as shown in the graphic below, four primary forces are pushing companies to adopt traceability systems: consumer demand, investor expectations, regulatory pressure, and business-related benefits (UNECE, 2023).

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What’s Driving Demand for Traceability?

Source: UNECE (2023). White Paper on Enhancing Traceability and Transparency for Sustainable Value Chains in the Circular Economy

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The growing pressure combined with the increasing decentralization of global supply chains has turned traceability into a strategic and operational priority. Commodities frequently move through multiple intermediaries, informal aggregators, and indirect sourcing channels, making visibility and control exceptionally difficult, particularly for companies operating in land-intensive sectors [(UNECE, 2023, §45)].

In this context, companies are expected to conduct due diligence not only during supplier onboarding, but also on an ongoing basis. The assessment criteria extend far beyond price and quality, now encompassing geolocation data, land-use history, and exposure to regulatory risks. However, most organizations lack access to consistent, farm-level data across all production plots and supplier tiers, making compliance verification difficult.

Why Is Full Traceability So Difficult?

Traditional supply chain systems were built for transparency, not spatial precision. As a result, collection points often do not register or verify the exact origin of goods. Instead, data is frequently aggregated at the municipal or regional level. In the absence of verifiable, georeferenced data, companies must rely on assumptions, incomplete records, or self-reported information, none of which meet the demands of regulatory frameworks, like EUDR.

This gap between regulatory expectations and the operational realities of fragmented supply chains is not merely theoretical, it is well-documented in applied research. A case study from Côte d’Ivoire offers a concrete illustration of just how difficult it is to map supply origin in practice, even with advanced methodologies and tools.

Example - Case in Point: Mapping Cocoa Supply Chains in Côte d’Ivoire

The study Transparency, traceability and deforestation in the Ivorian cocoa supply chain using the Spatially Explicit Information on Production to Consumption Systems (SEI-PCS) method reveals just how complex supply chain mapping can be. Researchers analyzed cocoa exports in Côte d’Ivoire by linking them back to cooperatives, licensed buyers, and subnational regions using five steps: trade data analysis, cooperative mapping, production estimation, and remote sensing of deforestation exposure, as illustrated in the graphic below.

Figure. Schematic of the cocoa supply chain in Cˆote d’Ivoire with Sourcing traced to cooperatives in yellow, i.e. exports linked back to disclosed cooperatives, also including the small volumes sourced from known licensed buyers; indirect sourcing in green, i.e. exports that could not be linked back to cooperatives or buyers (purchased through unlicensed buyers) for traders who disclosed their suppliers; unknown sourcing in blue, i.e. exports of untransparent traders who did not disclose their suppliers.

Source: IOP Science, Transparency, traceability and deforestation in the Ivorian cocoa supply chain.

While some traders disclosed direct sourcing from 710 cooperatives, much of the supply came through indirect routes or licensed intermediaries with only approximate location data. Even with sophisticated Monte Carlo simulations and satellite data, the study could only link cocoa back to departments, not to specific farms or plots. This underlines the gap between current traceability practices and the precision required for regulatory compliance.

🇧🇷 Similar challenges persist within Brazil’s agricultural supply chains.

Brazilian producers and exporters are facing increased pressure as both global and domestic regulations demand greater transparency and accountability regarding deforestation and land-use practices.

For example, recent investigations revealed palm oil cultivation on recently deforested Amazon land, highlighting ongoing risks related to deforestation and insufficient monitoring in the region’s supply chains. (Climate Change News, 2025).

These developments highlight the urgent need for precise, farm-level verification tools to ensure compliance with global and local regulations such the Brazilian Forest Code and EUDR.

The Challenge of Land-Based Traceability

Even with tools like satellite imagery and geolocation, several issues complicate field-level traceability, for example:

• Changing field appearance: Crop growth stages, cloud cover, and seasonal changes can distort images, making it difficult to segment land correctly.
  
  
• Short rotation cycles: Multiple planting and harvesting cycles per year mean recent images might not reflect current crops accurately.
  
  
• Irregular field boundaries: Fields often don’t have clear, straight borders and may contain multiple crop types, complicating automated mapping.
  
  
• Mixed agricultural practices: Partial field use or crop mixing by farmers challenges standard modeling approaches.

These factors combine to make accurate, reliable land-based traceability a complex and ongoing challenge for supply chain verification.

How We're Tackling This at Marvin with AI 

At Marvin, we combine advanced technology with deep expertise in land use and compliance to deliver real traceability, not just estimates. Our platform integrates satellite imagery, AI, and geospatial intelligence to map and monitor land with precision.

As our Geospatial AI Researcher, Rotem M., explains:
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‍“At Marvin, we don’t just estimate land use. We verify it with precision. We’ve built a geospatial intelligence platform that fuses satellite imagery, remote sensing, AI, and compliance expertise to deliver true traceability on the ground. We integrate computer vision and foundational models into our AI stack, enabling precise, scalable mapping, even in fragmented and fast-changing land. By applying the latest advances in geospatial and remote sensing AI, we transform raw satellite data into actionable insights built for real-world complexity. Whether it’s for supply chain compliance, deforestation tracking, or regenerative agriculture, Marvin is pushing the boundaries of what land intelligence can do.”

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At the same time, we recognize that technology alone is not enough. Each company operates within a distinct context, shaped by its supply chain, geography, and regulatory exposure. As Rotem emphasizes:

“We believe that true innovation happens at the intersection of advanced technology and expert thinking. While we integrate the latest AI tools into our platform, we don’t rely on them blindly. Our team brings deep domain expertise to the table, we interpret, adapt, and build upon what the technology provides. That’s why we’ve developed our own methodology, to tailor solutions to each client’s unique reality. Every supply chain, region, and regulation presents its own complexities, that’s why our technology has built-in local intelligence and global trade coverage, designed to mitigate environmental, compliance, and physical risks through tailored traceability solutions.”

This combination of advanced AI and tailored expertise is what enables us to turn raw satellite data into strategic, real-world action, as illustrated in the visual below.

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From Satellite to Strategy: How Marvin Turns Land Data into Actionable Insights

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This means our clients receive reliable, field-level insights directly tied to their supply chains, helping them stay ahead of regulatory requirements while opening new market opportunities. This level of precision allows our clients to demonstrate traceability with confidence, not estimation.

We don’t believe in shortcuts. We deliver clarity, precision, and confidence, helping you reduce risk, access new markets, and turn traceability into a competitive advantage.

If traceability is a priority for your business, let’s build the right path forward, together. Get a Demo.