Value Map

Value Map is a South Korean proptech company operating a big data and artificial intelligence-based platform for real estate, specifically targeting the often-opaque land and small-to-medium-sized building market. The company was founded in 2015 as Value Up Systems by CEO Kim Beom-jin, a certified appraiser who identified a critical lack of accessible and reliable data in the non-residential property sector. Frustrated by the outdated IT systems within the appraisal industry, Kim, who originally studied education, transitioned into property appraisal to gain specialized expertise before venturing into entrepreneurship. His direct experience with the information asymmetry that favored brokers and led to issues like predatory real estate practices fueled his mission to democratize property data.

The company launched its flagship platform, "Value Map," in July 2017, introducing a service that displayed actual land transaction prices on a map, a novel concept at the time. This addressed a significant market gap, as existing real estate platforms primarily focused on apartments. By leveraging a proprietary data analysis algorithm, Value Map was able to pinpoint the exact locations of properties from government-provided data, which often lacked specific land parcel numbers. The platform's utility in making the market more transparent has been a key driver of its growth, attracting over 570,000 monthly active users.

Value Map's business model is multifaceted, serving both individual users (B2C) and institutional clients (B2B), including financial institutions. Revenue is generated through several streams, including a membership model, fees for services like property registration and document viewing, and specialized data sales. The platform's core offering is a comprehensive database of real-time transaction data for land and buildings across South Korea, which users can search and filter. Beyond data provision, the company has expanded its services to include an AI-powered automated valuation model (AVM) with a 90% accuracy rate, which is utilized by financial institutions for assessing collateral recovery possibilities. Another key feature is an AI-based architectural design tool that allows users to virtually construct a building on a piece of land to check potential layouts and parking capacity.

Keywords: proptech, real estate data, South Korea, land transaction, building valuation, commercial real estate, Kim Beom-jin, automated valuation model (AVM), property technology, real estate analytics, land value, real estate investment, data platform, building transaction prices, real estate transparency, AI architectural design, property data services, small and medium buildings, commercial property platform, real estate market analysis