Land Price Intelligence
Land research for buyers and investors — comparable sales, guideline values and infrastructure context
For any plot, shows seller asking prices, actual nearby sale prices and government guideline values separately, plus an evidence-based estimate range that refuses to guess when data is thin.
Status: End-to-end demo for Karnataka. All plot, price and project data is synthetic, and no forecasting model is published. · Period: Dec 2025 – present · Source: Private repository.
Screenshots are not published yet. The architecture is shown below.
01Overview
A research tool that keeps three different numbers apart: what sellers ask, what nearby land actually sold for, and the government guideline value. Each is shown with its source and date. Estimates come from comparable registered sales, and the app says “insufficient data” rather than inventing a figure.
02The problem
Land buyers in India rely on asking prices and hearsay. Real transaction evidence, guideline values and upcoming infrastructure are scattered across sources.
03Who it is for
- Individual land buyers
- Small investors
- Advisers doing due diligence
04My role
Product definition, valuation logic, back end, web front end and mobile app.
05Implemented features
- Plot view with asking price, comparable sales and guideline value, each labelled with source and date.
- Estimate range from comparable sales, or an explicit “Insufficient data for a reliable estimate”.
- Locality price history and nearby infrastructure projects with their stage.
- Acquisition-cost, loan EMI and net-return calculators, plus user-chosen growth scenarios.
- Karnataka due-diligence checklist, comparison of up to four plots, a watchlist, saved searches and alerts.
06Engineering challenges and approaches
Honest estimates
The comparable-sales model is backtested and reports an evaluation. Below an evidence threshold it declines to estimate.
One loan engine in three languages
The Python, JavaScript and Dart loan engines are all checked against a shared fixtures file, so web, mobile and API produce identical amortisation results.
07Outcomes and current status
- Working end-to-end demo across API, web and mobile, with automated tests.
No usage or revenue numbers are published here unless I can verify them.
08Roadmap (not yet shipped)
- Real transaction and guideline-value data sources.
- AI price-prediction models, only once backtests justify publishing them.