Case Study – PropTech Scale‑Up

Transforming lease analysis and maintenance coordination with NLP and predictive analytics

Scale‑up PropTech with 2,000‑unit portfolio across major UK cities

Client

Scale‑up PropTech with 2,000‑unit portfolio across major UK cities

Timeframe

System delivered in 12 weeks

Impact

Vacancy rate
-15%
Response time
-35%
Portfolio yield uplift
+9%

Need

The PropTech scale‑up was drowning in lease documents and maintenance requests. Manual processing created bottlenecks that delayed tenant responses and increased vacancy periods.

Our Build

Our team deployed an NLP pipeline that parses lease agreements and extracts key terms automatically. Predictive maintenance algorithms analyze sensor data to anticipate property issues before they escalate. The system coordinates responses across the portfolio and prioritizes tasks by impact on tenant satisfaction and property value.

Outcome

Vacancy rates dropped by 15% and maintenance response times improved by 35%. The portfolio now generates 9% higher yields while tenants experience faster issue resolution and more transparent lease management.

"LayeredAI transformed our property management from reactive to predictive. We now anticipate issues before they impact tenants and can make data‑driven decisions about our portfolio."
Chief Technology Officer, PropTech Scale‑Up

Key Features Delivered

NLP Lease Parsing

  • • Automated lease term extraction
  • • Contract clause analysis
  • • Rent review scheduling
  • • Compliance monitoring

Predictive Maintenance

  • • IoT sensor data analysis
  • • Maintenance scheduling optimization
  • • Issue escalation algorithms
  • • Cost prediction modeling

Transform Your Property Management Operations

Discover how LayeredAI can help your PropTech reduce vacancies, accelerate maintenance, and maximize portfolio yields.