CEO & Founder, SciCrop® | Creator of InfiniteStack | AI, Data Analytics, Agribusiness, Food Industry, and Infrastructure

José Damico is a technology entrepreneur and executive based in São Paulo, Brazil, with a career that connects applied AI, deep software engineering, information security, distributed systems and data platforms. He is the CEO and Founder of SciCrop®, an AI and Analytics company focused on helping large agribusiness, food industry, energy, and environmental organizations transform operational data into predictive, scalable, and business-critical intelligence.

At SciCrop, José leads the company’s strategy to make AI a practical infrastructure layer for agribusiness and adjacent industries. His work focuses on enabling companies to optimize and predict complex processes, reduce costs, increase productivity, and improve decision-making across agricultural production, industrial operations, sustainability, logistics, trading, and corporate data governance.

SciCrop develops AI, geospatial analytics, data engineering, and integration solutions for large national and multinational companies. Its work spans satellite imagery, GIS, machine learning, industrial telemetry, IoT/IIoT, ERP and CRM data, climate data, market data, and operational intelligence.

José is also the driving force behind InfiniteStack, SciCrop’s AI and analytics platform for agribusiness and the food industry. InfiniteStack is designed as an enterprise-grade foundation for companies that need to integrate internal and external data sources, govern data access, accelerate analytics adoption, and operationalize AI in real-world environments.

InfiniteStack combines no-code and low-code capabilities with enterprise data architecture, supporting areas such as:

• Collect: data ingestion and integration from enterprise, field, industrial, climate, geospatial, and market sources.
• Automate: workflows, pipelines, orchestration, and process automation.
• Leverage: AI models, analytics, forecasting, optimization, and decision-support applications.
• Catalog: data discovery, governance, semantic organization, and controlled access.
• Observe: monitoring, telemetry, dashboards, and operational visibility.
• Track: traceability, lineage, usage, and auditability across data and AI assets.

The platform is built for cloud or on-premises deployment, allowing enterprise customers to maintain segregation, governance, and flexibility while still benefiting from SciCrop’s AI infrastructure and expertise.

José combines executive leadership with hands-on technical depth. Before founding SciCrop, he held senior technology, architecture, R&D, and security roles in companies such as IBM and Intel. His background includes software and hardware architecture, banking systems, distributed systems, information security, identity protection, biometrics, Android customization, single-board-computer appliances, and advanced Java systems.

This technical foundation shapes his current work: José approaches AI not as a generic trend, but as an engineering discipline that depends on data quality, integration, domain knowledge, governance, and measurable operational impact.

Over the last few years, José has also been building small, sustainable GPU clusters to accelerate AI adoption inside companies. His approach is pragmatic: instead of treating AI only as a cloud-based experiment, he has explored compact, energy-conscious, and enterprise-ready compute environments that allow organizations to train, fine-tune, and run AI models closer to their own data, infrastructure, and operational reality.

This work includes early experimentation with local and open models for business use, including DeepSeek and other LLMs capable of running in controlled environments. José has been especially focused on how local models can support privacy, lower inference costs, reduce dependency on external APIs, and make AI more accessible for companies that need domain-specific intelligence.

In agribusiness, José has also been a pioneer in training and adapting LLMs for agricultural knowledge. His work includes fine-tuning small language models with domain-specific datasets, exploring RAG architectures, LoRA-based training, quantization, and local inference as ways to bring generative AI into real operational contexts such as crop management, technical assistance, industrial analytics, and enterprise knowledge systems.

José’s main strengths are the ability to translate complex technology into business value, identify high-impact use cases, and build platforms that can move from experimentation to production. His work connects strategic vision, commercial positioning, product leadership, software architecture, and applied AI.

He is especially focused on:

• AI and data infrastructure for agribusiness and food companies.
• Enterprise adoption of machine learning, computer vision, geospatial analytics, and generative AI.
• Data governance, semantic catalogs, lakehouse architectures, and integration platforms.
• Domain-specific AI assistants, RAG architectures, and LLM fine-tuning for agricultural knowledge.
• Predictive models for yield, logistics, industrial traffic, climate impact, demand, prices, and operational risk.
• Sustainable and scalable technology for agriculture, environment, and industrial transformation.

José has been recognized in innovation and entrepreneurship initiatives, including international awards and deep open source contributions. He has also authored publications related to technology, learning systems, process scheduling, and knowledge transmission.

He is fluent in Portuguese, English, and Spanish, and actively works at the intersection of AI, agribusiness, entrepreneurship, education, and enterprise transformation.

José Damico is an AI infrastructure entrepreneur for the real economy. Through SciCrop and InfiniteStack, he is building the bridge between advanced artificial intelligence and the operational complexity of agribusiness, food production, energy, and environmental sectors. His work is grounded in a clear belief: AI only becomes strategic when it is connected to governed data, domain expertise, robust engineering, and measurable business outcomes.

• https://scicrop.com
• https://infinitestack.ai
• X / Instagram / Social: @josedamico
• LinkedIn: in/josedamico