Virginia Tech's College of Agriculture and Life Sciences set out to transform the Global Agricultural Productivity (GAP) Report from a static publication into an interactive digital platform that would make complex agricultural data more accessible, actionable, and valuable for policymakers, researchers, investors, and global development organizations.
Appnovation partnered with Virginia Tech and Google through a phased approach to define the product vision, design the user experience, establish the underlying data foundation, and build the first functional alpha platform using Google Cloud, BigQuery, and Looker.
The engagement has progressed from concept into active development, establishing the product, data, and technical foundation for a scalable agricultural intelligence platform and supporting stakeholder alignment and fundraising along the way.
The Global Agricultural Productivity (GAP) Report is a critical resource used by policymakers, researchers, investors, and development organizations to understand agricultural productivity trends around the world.
While the report contained valuable data, its static format limited exploration, comparison, and decision-making. Users could access information, but they could not interact with it, explore relationships across datasets, or investigate the factors influencing productivity.
Virginia Tech envisioned a modern platform that would transform the report into an interactive digital experience, bringing together multiple datasets, intuitive visualizations, and future AI-enabled capabilities to support better policy, investment, and research decisions.
Appnovation partnered with Virginia Tech and Google to guide the initiative from concept through implementation using an iterative, product-led approach.
The engagement began with stakeholder workshops and collaborative product definition to establish a shared vision for GAP IQ. Appnovation then designed an interactive Figma prototype that demonstrated how users could explore agricultural productivity data through an intuitive digital experience.
Building on that vision, Appnovation modeled and structured the underlying agricultural productivity data within BigQuery and demonstrated interactive analytical capabilities using Looker, creating the technical foundation required to support future platform development.
Today, Appnovation is developing the GAP IQ Alpha platform, transforming the approved experience into a functional application powered by Google Cloud technologies.
Key Highlights
- Product visioning and stakeholder co-creation
- Interactive UX prototype developed in Figma
- Agricultural data modeled and structured within BigQuery
- Interactive analytics demonstrated through Looker
- Custom Alpha platform currently under development
- Scalable Google Cloud architecture supporting future platform evolution
Rather than delivering only a prototype, Appnovation established the product, technical, and analytical foundation for GAP IQ while advancing the initiative into active platform development.
The phased approach enabled Virginia Tech to validate the product vision, align stakeholders, demonstrate technical feasibility, and move into development of the first functional version of the platform.
Outcomes
- Defined the long-term product vision for GAP IQ
- Established a scalable data foundation within BigQuery
- Demonstrated interactive exploration through Looker analytics
- Shaped a commercial strategy positioning GAP IQ as a financially sustainable model within the university, directing returns back into future research and scientific advancement
- Supported fundraising and stakeholder engagement through prototype demonstrations
- Progressed from concept to active Alpha platform development
- Created a scalable foundation for future AI-enabled capabilities and continued platform expansion
How AI Was Involved
AI has been part of the long-term vision for GAP IQ from the outset.
The platform is being designed to evolve beyond traditional reporting by enabling users to explore complex agricultural data through intelligent, interactive experiences.
Future phases will leverage Google Cloud AI capabilities to support guided data exploration, scenario analysis, natural language interaction, and AI-assisted insights, helping researchers, policymakers, and funding organizations better understand the relationships driving agricultural productivity.
