The most complete Malaysian property dataset. Refreshed daily.
Hartanahub runs a proprietary ingestion pipeline covering Kuala Lumpur, Selangor, and Putrajaya. We combine live auction data with millions of transaction comparables and cross-check against rental records — giving every agent and buyer the same quality of signal a major brokerage would pay a team of analysts to assemble.
Deep on Klang Valley. Not spread thin across Malaysia.
Every Hartanahub record is for a property in Kuala Lumpur, Selangor, or Putrajaya. Focus over breadth — we'd rather be the most accurate source in the Klang Valley than mediocre nationwide.
| Region | Live auction listings | Transaction comparables | Rental records |
|---|---|---|---|
| Kuala Lumpur | 5,600+ | 780K+ | 102K+ |
| Selangor | 8,900+ | 1.4M+ | 128K+ |
| Putrajaya | 300+ | 104K+ | 17K+ |
Data discipline, not vibes.
Fresh twice a day
Our pipeline refreshes at 4 PM and 6 PM MYT. New listings, price drops, and result changes surface within a ~2-hour window — you never show a client a listing that was called off yesterday.
Multi-signal verified
Every auction listing is cross-validated across multiple independent signals. Mismatches are flagged — so you never see a record where the reserve price contradicts the case type, or the address contradicts the postcode.
Geocoded with care
We run a primary geocoder with a fallback, and reject any coordinate that lands more than 12 km from the postcode centroid. 99.96% of upcoming listings have reliable coordinates for Near-Me search and the map view.
Compliance-first
We operate within a compliance-first posture — our data origins and pipeline details stay internal, our public surface stays on what we can guarantee: freshness, coverage, and accuracy on what you see.
How we compute the BMV score.
For each auction listing, we find the most relevant comparables by combining:
- Same mukim + same postcode — the primary geographic filter.
- Same property type category — terrace against terrace, condo against condo, not a blended median.
- Recency window — last 24 months, with exponential recency weighting.
- Size proximity — if built-up area is known, we prefer comps within ±25% of the listing size.
- Cross-check — we run a separate count against auction transactions in the same area. If auction prices materially disagree with the transaction median, we flag the listing as “trending” and display both numbers.
The result is a median PSF and a comparison against the listing's reserve price — the BMV score you see on every card. Agents see the full methodology per-listing in the “View comparables” modal.
See the data power your next deal.
Free forever for the comp overlay on every auction card.