About Hiva

Property decisions, grounded in evidence.

Hiva is a Singapore property intelligence platform. We aggregate public market data and turn it into a single, transparent score for every residential project — so buyers and investors can compare on evidence instead of agent spin and showflat hype.

Why we built it

Singapore has some of the richest public property data in the world — URA caveats, rental contracts, OneMap, HDB datasets. Yet most buyers still make six- and seven-figure decisions on a glossy brochure and a gut feel. The raw data is public but scattered, and reading it well takes work most people don't have time for. Hiva does that work: we collect the data, normalise it, and express it as factors anyone can understand and audit.

How is a Singapore condo scored?

Hiva scores every Singapore residential project from 0 to 100 using weighted public-data factors. Transaction dynamics carry the most weight, with accessibility, education, amenities, rental demand and market liquidity as supporting factors. Each factor is computed from official public sources — URA transaction and rental caveats, OneMap school and MRT proximity data — normalised into a sleeve score, then combined into one composite score per project. The composite is re-ranked both within a project's district and across all of Singapore, so a score of 72 always means the same thing wherever the project sits on the island. The factor weights are fitted on out-of-sample historical outcomes and vary by market segment (core, rest-of-central and outside-central regions), so each segment is judged on what has actually predicted performance there. No agent input, listing fee, or paid placement affects a project's score — only the underlying public data does.

The full factor weights and metric definitions are published — Hiva is not a black box. We continuously validate the model against out-of-sample forward returns and only ship changes that hold up.

Where the data comes from

What we stand by