Category: GeoAI / Platform Engineering
Client: Lead Architect & Developer | 2024–Present
Tagline: Natural-language interfacing with spatial data through Discrete Global Grid Systems (DGGS).

Architected and led development of a GeoAI platform enabling natural-language interaction with spatial data through DGGS-based global indexing.

Outcomes

• DGGS architecture: Built hybrid hexagonal global-grid indexing with automatic knowledge-graph generation for significantly faster spatial operations.
• Performance breakthrough: Delivered major I/O, query-time, and storage improvements with columnar Parquet and intelligent compression.
• AI-native spatial reasoning: Combined vector search with spatial operations for natural-language GIS querying.
• Enterprise deployment: Implemented single-command Docker orchestration for cloud and on-prem installs.
• QGIS integration: Added native plugin support for real-time hex visualization and interactive spatial analysis in existing GIS workflows.
• Technical innovation: Combined DuckDB with PostgreSQL/pgvector for high-throughput, memory-efficient processing.

Stack / Systems

DGGS · H3 · QGIS · DuckDB · PostgreSQL/pgvector · Docker · Vector search