Introducing Marco AI: The World's First AI Co-Pilot for Green Supply Chain Management

Artificial Intelligence (AI) is rapidly becoming an integral part of manufacturing, reshaping industries with innovations like digital twins, quality control systems, and advanced supply chain management. Among these, AI copilots stand out for their potential to transform complex operations by working alongside human operators, guiding them through processes, and reducing costly errors. With the global market for AI in manufacturing projected to grow from $3.2 billion in 2023 to $20.8 billion by 2028, it’s clear that these copilots will play a critical role in the future of industrial operations.

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Imagine creating complex supply chain workflows as effortlessly as typing a few words. That’s the promise of generative AI (GenAI)—and it’s not just a distant vision. At Finboot, we’re bringing this to life with our latest innovation, MARCO AI—an AI copilot built into our flagship MARCO Track & Trace platform. Announced on May 8, 2025, this marks a major step in our broader AI strategy, designed to cement Finboot’s position as a leader in digital traceability for greener, smarter supply chains. Our goal is simple: use AI to boost efficiency, speed up processes, and improve transparency across global supply chains.

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But this isn’t just a software upgrade—it’s a breakthrough in how businesses approach supply chain management. With MARCO AI, setting up complex traceability systems can now be done in seconds, without the need for extensive coding or technical expertise. Our CEO and co-founder, Juan Miguel Perez, recently joined me, Mario Navarro, Finboot’s software engineer and AI lead, to demo this powerful new tool. In this blog, I want to take you behind the scenes of that demo and share why this technology is set to redefine supply chain automation.

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Introducing MARCO AI: A Game-Changer in Digital Traceability

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As explained in the recent announcement, when Finboot first launched MARCO Track & Trace in 2018, our goal was to provide businesses in carbon-intensive sectors with a powerful, flexible, and transparent solution for green supply chain management. This has enabled our customers to decarbonize their operations by accurately tracking and verifying the origin of their low-carbon, renewable, and circular products. However, as Juan Miguel highlighted during the demo, staying ahead in this rapidly evolving field means continuously pushing the boundaries of innovation. That’s exactly what we’ve done with MARCO AI.

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MARCO AI is designed to make complex supply chain configurations as simple as sending a text. Our no-code MARCO Track & Trace console already allowed customers to build bespoke workflows without writing custom code, significantly reducing configuration time. But with MARCO AI, we’ve taken this a step further. Now, users can simply describe their supply chain workflows in natural language, and our AI copilot takes care of the rest.

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Building the “AI-Powered Bio-Refinery”—A Real-World Example

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During the demo, I built an 'AI-Powered Bio-Refinery' in real time to showcase the capabilities of MARCO AI. Here’s a quick overview of how it worked:

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1. Creating the Supply Chain – I prompted MARCO AI to create a supply chain named “AI-Powered Bio-Refinery” with two workflows and two assets. 
   
   1. The first workflow, “Raw Materials”, processes an asset called “Feedstock”, with properties like PO number, Sustainability Declaration, and Type of Raw Material. 
   2. The second workflow, “Production”, processes the asset 'Final Product' with steps for biorefining and product dispatch, including critical attributes like Production Date, ISCC Certificate, and CO2 Emission Reduction.
2. Seamless Configuration – Within seconds, MARCO AI generated a complete digital workflow structure, linking assets and steps without requiring any manual coding. This reduced the time required to configure a typical supply chain from several hours to just a few clicks. As Juan highlighted, this capability can reduce configuration times by over 98%, enabling customers to achieve faster time-to-value and maximize ROI.
3. Real-Time Execution – After setting up the workflows, we demonstrated how easily users can input data and execute processes, validating each step along the way. This streamlined approach not only enhances efficiency but also reduces the risk of costly errors and misconfigurations. The AI copilot intelligently links each step, ensuring seamless data flow and reducing manual interventions.

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The Technical Advantage of MARCO AI

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What sets MARCO AI apart from other AI solutions is its deep integration with our MARCO Track & Trace platform, which has been refined over years of real-world use in industries like energy, chemicals and steel This means that the AI is not just a generic assistant, but a specialized copilot designed to handle the complexities of digital traceability in highly regulated and carbon-intensive sectors.

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Additionally, MARCO AI’s architecture allows it to adapt to changing business needs, continuously learning from past workflows to optimize future processes. This adaptability is vital for industries undergoing rapid digital transformation, where flexibility and real-time decision-making are essential for maintaining a competitive edge.

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Looking Ahead

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As Juan Miguel mentioned in the video, we are currently in the testing phase for this powerful new feature, working closely with a select group of early adopters to fine-tune the experience. Our aim is to reduce supply chain configuration time by over 98%, accelerating time to value and maximizing ROI for our customers.

If you’re a current customer, this is a game-changer for your operations. If you’re not yet part of the Finboot ecosystem, now is the perfect time to explore how MARCO AI can transform your approach to digital traceability and sustainable supply chain management: contact us here.