LettingsCopilot assesses tenant enquiries for intent and affordability — flagging missing income data, guarantor gaps, and low-fit leads before your team wastes time on them.
Built for UK letting agencies
The Problem
Intent masked by politeness
Friendly enquiries can sound promising while carrying no usable signal. Your team wastes time chasing tenants who were never likely to proceed.
Affordability issues spotted too late
Agents often discover income problems after viewings and follow-ups have already happened — costing time, effort, and pipeline clarity.
Critical details never collected
Employment status, household income, guarantors, and occupancy details are often missing from initial enquiries.
Features
Intent Assessment
Every enquiry classified as High Intent, Needs Info, or Low Fit based on clarity, urgency, and completeness.
Affordability Signal Detection
AI assesses household income, partner income, and guarantor context against the tenant's stated budget.
Missing Information Alerts
Amber warnings surface exactly what's missing — income figures, guarantor details, move-in dates, and more.
Smart Reply Drafts
Generate personalised replies informed by the lead's affordability context and missing information.
Centralised Pipeline
All inbound tenant enquiries in one searchable dashboard with intent and affordability visibility.
One-Click Re-qualification
Re-run AI analysis instantly when applicants provide new income or guarantor information.
How it works
Tenant submits enquiry
Name, budget, income, employment, and guarantor details captured in one form.
AI assesses intent
High Intent, Needs Info, or Low Fit assigned based on enquiry quality.
Affordability gaps flagged
Household income checked against affordability expectations. Missing data surfaced instantly.
Reply draft generated
Contextual response ready to send by email or WhatsApp.
Pipeline stays clean
Your team sees which leads are actionable before wasting time on dead-end enquiries.
Product Demo
A quick walkthrough of how agencies can assess tenant intent, review affordability signals, and generate contextual replies in seconds.
3-minute founder walkthrough
See it in action
Total
4
High Intent
2
Needs Info
1
Low Fit
1
| Name | Intent | Affordability | Score | Budget | Date |
|---|---|---|---|---|---|
| Sarah Mitchell | High Intent | Pass | 85 | £2,200 pcm | 2 May 2026 |
| James O'Brien | High Intent | Pass | 74 | £950 pcm | 5 May 2026 |
| Amira Hassan | Needs Info | Maybe | 55 | £1,100 pcm | 9 May 2026 |
| Marcus Webb | Low Fit | Fail | 28 | £1,400 pcm | 10 May 2026 |
Intent assessed. Affordability surfaced. Reply drafted. All in seconds.