ATIO Knowledge Base at FAO

FAO's Agrifood Systems Technologies and Innovations Outlook (ATIO) Knowledge Base brings agrifood innovation records together for discovery, comparison, and decision-making. My work examines how people find and use those records.

I contribute within an existing platform built on Drupal 10, where Solr supports structured and faceted search, Milvus supports vector-based semantic similarity, and Gemini via Vertex AI supports AI enrichment. This is the system context I work within; I did not build its retrieval pipeline or vector index.

The public knowledge base contains thousands of technology and innovation records.

As an Innovation Accelerator Intern in FAO's Office of Innovation (Jun 2026–Present, Rome), I lead the user-engagement workstream and conduct behavioral analysis for the ATIO Knowledge Base.

• Use GA4 to study entry points, search behavior, device use, and movement from profiles into related content.
• Translate behavioral evidence into UX and analytics requirements.
• Evaluate AI-enrichment quality and contribute evidence for prompt and metadata improvements.
• Support search, visualization, and taxonomy-aware discovery work with colleagues responsible for Drupal, taxonomy, data harvesting, and AI pipelines.

Internal systems, non-public data, and restricted implementation details are intentionally omitted.