Mayordomo

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About

The problem it solves Every minute, more than 1.3 million cups of coffee are consumed worldwide. More than 9,000 of those cups come from Latin America. In that same minute, more than one hectare of forest is lost to sustain this demand. And most worryingly, farmers receive less than 10% of the value they pay for that cup. Latin America is a global agri-food powerhouse. According to ECLAC, in 2022 the region reached record figures in agricultural exports, exceeding $340 billion, driven by growing international demand for food. However, this economic boom hides deep inequalities and serious environmental impacts: Economic inequality: In Latin America, between 70% and 85% of the final value of agricultural products remains in the hands of intermediaries, exporters, and marketers. Farmers, who bear the greatest risk, receive the lowest profit margin. Biodiversity loss: According to the WWF, between 1970 and 2020, Latin America lost 95% of its average wildlife population, and the UN warns that 33% of the planet's soils are already degraded, and by 2050 we will need 60% more food to supply the world's population. We NEED to develop a regenerative agricultural model that responds to growing consumer demand without continuing to destroy the planet. And this is not just an environmental need: various studies show that between 60% and 70% of global consumers are willing to pay more for products that guarantee sustainability and fair treatment for those who produce them. At Mayordomo, we work to build a truly regenerative food chain. Using artificial intelligence and blockchain technology, we seek to trace the entire value chain of agricultural products exported from Latin America and certify sustainable, fair, and transparent production models.

How it's made

Challenges we ran into 1. Low Technology Adoption by Farmers One of the main obstacles we encounter is the low adoption of technology in Latin American agriculture. To overcome this barrier, we developed an artificial intelligence agent that communicates with producers through a well-known and widely used channel: WhatsApp. This agent functions as a conversational assistant, capable of gathering key information about the production process, asking simple questions, guiding farmers step-by-step through the transition to regenerative practices, and providing ongoing technical support. 2. Need for Multiple Specialized Agents The agricultural production process involves different stages and dimensions that require specialized attention. Therefore, we developed an architecture of multiple artificial intelligence agents, each with a specific role: Legal Agent: Supports report generation, information processing, and document management necessary to obtain environmental, social, or quality certifications. Operations Agent: Monitors and analyzes the phases of the production process in real time, generating alerts, recommendations, and suggestions for continuous improvement. Environmental stakeholder: Evaluates the ecological impact of each agricultural practice, measuring variables such as land use, emissions, biodiversity conservation, and ecosystem regeneration. 3. Actively involve the consumer One of the most important challenges, especially in the context of the challenge proposed by Base Batch, was finding a way to actively involve the consumer in the development of this regenerative supply chain. To achieve this, we designed a tokenization model, in which the consumer can: Directly invest in the transition from a conventional to a regenerative agricultural model. Establish a direct link with the producer, accessing verified information about the practices employed. Become part of a regenerative ecosystem, where their purchasing decision has a direct impact on the land