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

How should you decide between Singapore condos?

Comparing Singapore condos on asking price or a single agent review misses the factors that actually predict how a project performs. Before committing, weigh three things together: whether recent transaction prices are trending up or flat within the project's own district and market-segment cohort, whether rental yields support your holding-cost assumptions if you are not owner-occupying, and whether the accessibility and amenity profile matches how you or your tenants will actually live day to day. A well-priced unit in a project losing rental demand can underperform a fairly priced unit in a project gaining momentum on transport and school access. Hiva's screener and compare tools surface all three side by side, drawn from the same public URA, OneMap and rental-contract data behind the composite score, so the comparison stays evidence-led rather than brochure-led. This is a decision-support framework, not financial advice; every buyer's constraints and market timing differ.