Question 1

Is PropertyLens a licensed valuation service?

Accepted Answer

No. PropertyLens is an AI-powered research and analysis tool, not a licensed valuation service. Our predictions are estimates based on publicly available data and AI analysis. They should not be used as a substitute for a formal property valuation by a certified valuer, nor as financial advice. Always consult qualified professionals before making property decisions.

Question 2

Where does the data come from?

Accepted Answer

All our data is sourced from publicly available datasets and official APIs. This includes historical sales data from Domain.com.au and PropTrack, demographic data from the Australian Bureau of Statistics Census, planning overlay data from local council open data portals, economic indicators from the Reserve Bank of Australia, and development application data from Planning Alerts. We do not use any proprietary or private data sources.

Question 3

How accurate are the property price predictions?

Accepted Answer

Property price predictions are inherently uncertain — no model can perfectly predict what a buyer will pay. Our system tracks prediction accuracy against actual sale prices, and we publish these metrics transparently. Predictions include confidence scores and price ranges to reflect uncertainty. Typical accuracy varies by suburb and property type, and we cap confidence scores at 85% for houses and 80% for units to reflect real-world limitations.

Question 4

Which cities and suburbs are covered?

Accepted Answer

We are expanding across major Australian cities. Brisbane is currently live with 33 inner suburbs across four zones. Gold Coast is launching mid-2026, with Sydney and Melbourne following in late 2026. Each city launch covers inner suburbs with sufficient comparable sales data to produce meaningful predictions. Visit our Cities page for the latest coverage details.

Question 5

How does the AI component work?

Accepted Answer

We use Claude by Anthropic, a leading safety-focused AI model, to analyse property descriptions, comparable sales data, feature adjustments, and suburb context. The AI provides qualitative analysis including predicted price, reasoning, market sentiment, value drivers, and risk factors. The AI prediction is blended with statistical analysis (comparable sales and feature engineering) to produce the final estimate — it does not operate in isolation.

Question 6

Can I use this for construction cost planning?

Accepted Answer

Our construction cost estimation provides indicative costs for common renovation scenarios — raise and build under, second storey additions, and basement conversions. Costs are based on industry rate databases adjusted for inflation using ABS Producer Price Index data. These estimates are starting points for budgeting, not fixed quotes. Actual costs will vary based on site conditions, builder selection, material choices, and council requirements. Always obtain multiple quotes from licensed builders.

Question 7

What planning constraints does the system check?

Accepted Answer

We check local council planning overlays relevant to each city, including character housing provisions, heritage listings (local and state), flood overlays, landslide hazard, and biodiversity overlays. We also monitor Development Application activity through Planning Alerts. The specific overlays checked vary by city as each council has its own planning scheme. These constraints significantly affect what you can build and the approval pathway required.

Question 8

Is my data private?

Accepted Answer

We analyse publicly available property data — we do not collect, store, or sell personal information beyond what you voluntarily provide through our contact or waitlist forms. Property analysis is based on public listing data, public sales records, and public planning data. See our Privacy Policy for full details.

Privacy Policy

1. About This Policy

2. Information We Collect

2.1 Information You Provide

2.2 Information Collected Automatically

2.3 Property Data

3. How We Use Your Information

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