AI Rental Comp Analysis
The Problem
“Slow, inconsistent rental comp selection and pricing”
Organizations face these key challenges:
1
Data fragmentation and inconsistency across MLS, portals, and internal PMS/CRM systems (missing concessions, inaccurate sqft, outdated status)
2
Subjective comp selection and adjustments that vary by agent/analyst, causing inconsistent underwriting and pricing decisions
3
Slow turnaround that delays listings, renewals, and investment committee decisions, increasing vacancy and opportunity cost
Impact When Solved
75–90% reduction in time spent generating rental comp sets and adjustment narratives10–20% faster lease-up and fewer price reductions through better initial rent positioning1–3% improvement in realized rent and tighter underwriting variance with confidence-scored recommendations