Case Study: a US-based distribution company achieves geospatial analysis in seconds with Six Feet Up

US-based Distribution Company turns 30-minute geospatial analysis into seconds with Six Feet Up

The customer, a US-based distribution company, faced a challenge with a slow and unreliable geospatial recommendation tool built as a proof-of-concept in R/Shiny. The vendor, Six Feet Up, was engaged to re-architect the system, which took 20-30 minutes per request and could not handle concurrent users during peak seasons.

Six Feet Up rebuilt the application using Python, Django, React and PostgreSQL with PostGIS on Kubernetes. Their solution minimized data read per request, moved expensive computations off the critical path, and incorporated real-world constraints. The results were transformative, reducing the 20-30 minute workflow to mere seconds and making the system reliable and production-ready.