A valuation you can explain line by line.
Property Valuation Desk gives valuers a transparent, evidence-based price, a clear confidence score, and a branded client pack in minutes. The maths is deterministic, and AI only helps write the letter.
The problem
A good valuation needs evidence, judgement and a clear story for the client. The evidence was scattered, and the story was built by hand every time.
Evidence everywhere
Sold prices, live listings, rental data and floor areas all sat in different systems.
Asking vs. achieved
Asking prices are ambition, while sold prices are fact. Mixing the two quietly inflates a valuation.
Client packs by hand
Every valuation meant assembling comparables, writing a letter and formatting a branded document from scratch.
The system
Data comes in on a schedule, the engine does the maths, the valuer makes the call, and only then does AI help with the writing.
Every adjustment, in plain sight
Before a comparable sale counts, it's made fair to the property being valued. The valuer can see exactly how each one was adjusted.
Older sales are brought up to date using local price growth.
Bigger homes trade at a lower rate per sq ft, so rates are adjusted for size.
Small, explicit adjustments for freehold vs. leasehold flats.
Confidence you can see
Every result carries a confidence score built from five measurable ingredients. When confidence is low, the app says so and flags the valuation for manual review.
Decisions that matter
Guardrails that keep a pricing tool honest, especially once AI is involved.
Sold and asking are never averaged
Achieved prices drive the valuation. Asking prices get their own separate view. Marketing ambition can't quietly change the number.
Maths first, AI second
The engine calculates every figure. AI only drafts the letter from facts it's given, and the valuer edits and approves it.
AI is told what it can't say
Use only the supplied figures, invent no amenities or comparables, and never blend sold with asking. If the AI is unavailable, it fails visibly instead of making things up.
Show uncertainty, don't hide it
No artificial narrow ranges. Thin evidence or a very wide range triggers manual review instead of false precision.
Inferred data is labelled
If floor area has to be estimated, it's flagged, and confidence drops accordingly. Nothing is invented silently.
Tested like a model, changed like one
Backtested walk-forward, so every estimate only uses evidence from before that sale. All coefficients live in one place and are re-tested before any change.
Where else this works
Any workflow that goes from evidence to an estimate, then to a document a client can trust.
- Pricing & quoting
- Insurance underwriting
- Lending decisions
- Used-vehicle valuation
- Procurement estimates
- Professional services proposals