Internal Ops UX — Ford Foundation
Modernizing institutional memory. A UX transformation of an 80-year grantmaking archive, applying NLP to turn millions of static documents into a discoverable knowledge engine.
"Institutional knowledge was trapped in siloed legacy repositories. The challenge was preventing 'organizational amnesia' by transforming 80 years of unstructured PDFs and grant letters into a searchable, semantic database without overwhelming non-technical Program Officers."
How it Works
A unified knowledge retrieval architecture. We consolidated disparate SQL databases and file servers into a single search index. The pipeline utilized NLP entity extraction to automatically tag documents with 'about-ness' (themes, regions, demographics), enabling semantic retrieval across decades of unstructured text.
- 1Taxonomy & Metadata Schema
- 2Entity Extraction Logic
- 3Intranet/SharePoint as Semantic Search Frontend
- 4Grantmaking data ingestion pipeline
Designing the Interface
Designing for 'Sense-Making,' not just search. I moved beyond simple keyword matching to design a faceted discovery interface. The UX introduced 'Topic Clusters' and 'Smart Filters' that allowed officers to drill down by era, grant type, or impact region, reducing the cognitive load of sifting through legal archives.
- 01
Consolidated 4 disparate legacy repositories into a Single Source of Truth for grant history.
- 02
Reduced document retrieval time for Program Officers by introducing NLP-driven semantic facets.
- 03
Recovered "lost" institutional knowledge by digitizing and tagging 80 years of physical and digital artifacts.
- 04
Brought about cross-departmental alignment on knowledge management best practices.