Case studies
Recent work.
Numbers represent observed change inside the engagement window. Names withheld at client request.
Multifamily
From benchmark to rollout: how AI improved the revenue cycle for a major portfolio
An institutional-grade AI implementation that reduced delinquency by 100 basis points, accelerated collection speed by 41%, and delivered predictable cash flow across a major multifamily portfolio. Benchmarked in New York. Scaled to California.
- Delinquency rate: 3.7% → 2.7% (−100 bps)
- Days to 95% collected: 17 → 10 (−41%)
- Year over year variance spread: 5pp → 3pp (−40%)
Cut lead response time from 41 minutes to 2
Replaced a manual round-robin with an AI router that scores by buyer fit and pages the right agent in Slack. Six-week build.
- Avg first response: 41 min → 2 min
- Lead-to-meeting rate: 8.4% → 14.1%
- Coordinator hours / week: 22 → 6
Reduced first-touch maintenance turnaround by 63%
Built a triage agent that reads resident messages, classifies urgency, opens work orders in AppFolio, and drafts the first vendor outreach. Eight-week build.
- First-touch turnaround: −63%
- Resident NPS: +18
- Work-order classification accuracy: 94%
Screened 217 deals in 9 weeks vs. 38 the prior quarter
Memo draft pipeline cut analyst time per deal from 4 hours to 35 minutes. IC decisions still human; the funnel widened.
- Deals screened (9 wks): 217 vs. 38 prior quarter
- Analyst time / deal: 4 hrs → 35 min
- Memo template adherence: 100%