Assignment Matching by Geography

Manual geographic matching forces coordinators to cross-reference location data from memory or separate records, producing suboptimal pairings that increase volunteer travel and slow assignment acceptance. Automated proximity ranking cuts coordinator decision time, reduces travel burden on peer mentors, and shortens the gap between assignment creation and dispatch - directly improving support response times for contacts in need. For Blindeforbundet, which operates across wide regional geographies with many active mentors, this ranking is an operational necessity rather than a convenience. Better geographic matching also reduces burnout risk by distributing assignments more fairly across the mentor pool based on objective proximity data.

The backend exposes a ranked suggestions endpoint (GET /api/v1/assignments/:id/suggested-mentors) that applies eligibility filters (active status, org membership, module-enabled) before computing Haversine distances between the contact's registered location and each candidate's peer_mentor_locations record. Computation runs entirely server-side to avoid exposing raw coordinates to clients beyond what is necessary for display. A graceful fallback returns an unranked eligible-mentor list when location data is absent for either the contact or the mentor. All location lookups are recorded in the organization's audit log per the platform's audit requirements. The geographic-map-view module toggle gates both this service and the map UI; tenants with the module disabled receive 403 on the suggestions endpoint.