After 6 months in production:
The Challenge
Propty, an Amsterdam-based PropTech startup, identified a critical pain point in the Dutch rental market: property managers were spending hours manually matching tenants with suitable properties. The process was inefficient, error-prone, and created bottlenecks that frustrated both property managers and prospective tenants.
The key challenges were:
Manual matching overload โ Property managers reviewing 50+ applications per property, taking 2-3 hours per listing
Subjective decision-making โ No standardized criteria led to inconsistent tenant selection
Missed opportunities โ Good tenants fell through cracks due to delayed responses
Our Approach
We partnered with Propty to build an AI-powered property matching platform that would automate tenant-property matching while maintaining transparency and compliance.
We started by deeply understanding the problem:
Key insight: The matching problem wasn't just about filtering โ it was about prioritization . Property managers needed help identifying the best matches quickly, not just eliminating poor fits.
We designed a multi-component AI system:
We built the platform using our proven stack:
The Outcome
After 6 months in production:
40% reduction in time spent on tenant-property matching
25% improvement in tenant retention (better initial matches)
3x faster time-to-fill for vacant properties
10,000+ properties now on the platform
โ"Selectcursor didn't just build us software โ they built us a competitive advantage. Our property managers now focus on relationships instead of paperwork. The AI matching has become our secret weapon in a crowded market."โ
Technologies Used
Timeline
- We started by deeply understanding the problem:Phase 1: Discovery & Validation (2 weeks)
- We designed a multi-component AI system:Phase 2: AI Architecture Design (2 weeks)
- We built the platform using our proven stack:Phase 3: Development & Training (6 weeks)
- We launched with a controlled rollout:Phase 4: Launch & Iteration (4 weeks)