The challenge: 4,600 calls a month, 12-hour callback times, and no room for proactive management

Cornerstone Property Management manages 1,200 residential properties across Greater London on behalf of landlords and institutional investors. Their property management team of seven handled all tenant communications: maintenance requests, lease queries, payment issues, access arrangements, and complaints.
4,600+ calls per month. Average callback time for non-urgent queries: 12 hours. Maintenance requests submitted by phone were frequently incomplete (wrong property address format, vague fault descriptions), causing delays and repeat contacts. The team's entire capacity was consumed by reactive phone work, leaving no time for proactive property management.
London's diverse tenant base meant calls came in a range of accents and dialects. The team needed a solution that could handle callers from every background clearly and patiently.

The solution: 24/7 tenant support across 1,200 properties, with property-specific fault context built in

Thrumble AI handles all inbound tenant calls 24 hours a day. The AI identifies the tenant, confirms their property, and resolves or routes based on the inquiry type.
For maintenance: structured fault capture with property-specific context (the AI knows the building type, common issues, and approved contractor list for each property). Work orders are created with full detail and dispatched automatically.
For lease, payment, and general queries: the AI provides instant answers from Cornerstone's knowledge base, processes payment references, and schedules viewings or inspections.
The voice model uses clear, neutral British English, designed to be easily understood by London's diverse tenant population.

The results: The numbers speak for themselves

• 4,600 tenant calls handled per month across 1,200 properties.

• 90% resolved autonomously on the first call.

• Maintenance work order completeness: 97%, up from 62%.

• Tenant response time: instant (24/7), down from 12-hour average.

• Contractor first-visit resolution improved from 59% to 83%, directly attributed to better fault data.

• The AI handles calls from tenants with a wide range of accents and dialects, with a 96% successful interaction rate.

The commercial impact: £310K saved. £180K in avoided repeat call-out charges. Landlord retention up 11%.

£310,000 per year in property management staffing costs saved.
Landlord retention improved by 11%, as the quality and speed of tenant management directly impacts landlord satisfaction.
The improvement in contractor first-visit resolution saves an estimated £180,000 per year in repeat call-out charges across the portfolio.
Deployed in 6 weeks.

4,600 calls. 1,200 properties. 90% resolved first time. London's most diverse tenant base, handled 24/7.