Why Is There No Price Competition in a 22-Trillion-Won Market?
A renovation can be one of the biggest transactions in a person's life. And yet, in this 22-trillion-won market, price competition barely works. Every contractor measures and formats its quotes differently, so a consumer has no way to place two quotes side by side and compare them objectively. In that gap, surprise charges and defect disputes become routine.
The burden isn't the consumer's alone. Contractors, too, lose one to three days of opportunity cost on every single quote. The information asymmetry is burning both sides of the deal at once. With close colleagues, I decided to tackle this with standardization and AI.
The Core Is Separating Measurement From Estimation
The heart of the solution is to separate measurement from estimation. When an inspector measures a site once, a single mobile LiDAR scan automatically generates 73 inspection items, a 3D mesh, 200 photos, and a risk grade. The factual basis for a quote is no longer different for each person -- it is produced on top of one standard.
On that shared basis, five vetted contractors compete only on unit price and margin over the same item structure. The consumer compares five quotes side by side in a single meeting. It is what makes renovation, for the first time, a market you can compare.
The Core of AX Is Building a Common Basis for Comparison
A principle I've stressed throughout my AX consulting repeats itself here. In a market with information asymmetry, the way to win is not better sales but building the common basis that makes comparison possible in the first place. The role of AI is exactly this: to generate that standard layer automatically from a single scan.
When you structure the ambiguous, hands-on judgment work into a machine-readable, identical item system, competition and comparison finally become possible on top of it. The principle I've preached in consulting -- this time I'm testing it myself, as a founder.
Built 100% With Vibe Coding, From the MVP On
The way we build is AI-native, too. From the MVP on, we are writing 100% of the code with Vibe Coding. The person sets the goals and the judgment criteria; execution is left to AI. That is how even a team that isn't large can push a real product forward.
We are currently running an alpha and raising a seed round. There is still much to prove, but the direction is clear: to turn a market locked in information asymmetry into one you can compare -- for the first time -- through standardization and AI.