Case Studies · 8 min read
GeoIQ Deep Dive: From Bore Logs to Searchable Subsurface Intelligence
How Subterra turned fragmented geotechnical inputs into a clearer, more searchable intelligence workflow through GeoIQ.
GeoIQ exists because raw bore logs, subsurface notes, and geotechnical context are hard to use when they stay trapped in fragmented documents and tables. The goal was not to create another visualization shell. The goal was to make difficult subsurface information easier to inspect, search, and explain in an operational workflow.
Key Results
- Teams moved from raw logs and fragmented context toward a more searchable workflow.
- The output became easier to communicate internally and externally because the product emphasized clarity, not just technical complexity.
- GeoIQ became a public proof asset that demonstrates how Subterra handles domain-specific AI product work.
Challenge
- Geotechnical data was useful, but too much of the interpretation burden stayed on the human reviewing raw source material.
- Information lived across multiple formats, which made it harder to compare records and explain findings clearly.
- The workflow needed something more operationally useful than static exports or isolated visuals.
Solution
Subterra built GeoIQ as a geotechnical intelligence product focused on usable interpretation.
- Raw subsurface inputs were translated into clearer spatial outputs.
- Search and review were designed around the way teams actually inspect data, not just around a rendering engine.
- The product positioned machine learning as support for interpretation, not as a black box replacing judgment.
Tech Stack Applied machine learning · Geospatial data processing · Custom AI product engineering · Domain-specific workflow design
