The Big Data unit integrates land registry, transaction, listing, zoning, demographic, traffic, disaster, commercial, debt, and ownership data to form one of MyGo Lab’s core competitive moats.
The mission of the Big Data unit is to clean, classify, standardize, and reconstruct fragmented and inconsistent real estate data into a data foundation usable by AI and financial models.
Without high-quality data, there can be no trustworthy AI. Without structured data, there can be no institutional-grade risk control. Without a cross-market data architecture, MyGo Lab cannot replicate its capabilities across Japan, Thailand, Malaysia, and global markets.
Big Data research matters because it is the foundational fuel for AI valuation, ownership intelligence, risk models, transaction platforms, capital products, and RWA applications. By continuously accumulating, cleaning, classifying, and reconstructing real estate data, MyGo Lab builds a long-term and difficult-to-replicate data moat.
Integrating land, buildings, parcel numbers, area, and rights data
Building relationship graphs between owners and assets
Integrating mortgage, second mortgage, private mortgage, and foreclosure-related signals
Integrating zoning, planning, FAR, and building restrictions
Standardizing historical transaction and market data
Cleaning platform and agent listing information
Identifying high-net-worth owners from asset holdings and behavior
Building replicable data models for Taiwan, Japan, Thailand, and Malaysia