Reevl

Summary

A real estate terminal that reads Korean apartments like listed stocks. I designed it, built it, shipped it, and still run it – on my own.

5,000+

Monthly active users

Launched July 2026

64,817

Public pages

Standalone routes for search

2,054 / 2,380

Commits written with AI

Jul – Sep 2026

Role – research · information architecture · design system · frontend · data · operations (solo)

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Overview

Reevl is a real estate terminal for Korean apartments. It treats apartment complexes like listed stocks – each with a price chart, a change rate, and a value – so the market state is readable at a glance.

1. 01Design

   

   Figma

   • 140 variables
   • 23 components

2. 02Buildprivate

   2,380

   GitHub

   • 2,380 commits
   • Jul 1 — Sep 18

3. 03Ship

   

   reevl.co.kr

Research

Reevl's research came less from interviews than from operating data and what users pointed out. After launch, the signals that arrived every day became the reasons for the next decision.

• 366 commits started from a user's remark – 16% of all commits. One-line reports like "the hover effect gets cut off" (its cause changed three times) or "going back drops me on the apartment list" each became a fix.
• Behaviour data (Microsoft Clarity) – 89% of visits came from Naver, 79% of devices were mobile. Those two numbers set the product's priorities: mobile first, Naver search first.
• Eight data sources – MOLIT transactions, K-apt, the Korea Real Estate Board, KOSIS, the Bank of Korea, V-World, SchoolInfo, and Cheongyak Home: 45,695 apartment complexes and 11 million transactions brought into one screen's language.

Key decisions

Four decisions that made the product what it is – what was decided, why, and what came of it.

1. 01Show the state of the market, not the price of a home

   Where the whole market is moving should read before any one complex's price. So the direction was a Bloomberg terminal's information density with the cleanness of Toss Securities.

   →One home screen carries the market briefing, the sales and jeonse indices, and the complex rankings.Home screen

2. 02Up is red, down is blue – on every screen, no exceptions

   It follows the convention Korean market users already read by. Green never means “up”.

   →Direction colours exist only as design-system tokens (up · down), so no screen drifts.Design system

3. 03One screen, three shells

   The same information appears as a docked panel on desktop, a full screen on phones, and standalone pages for search.

   →That one structure produces 64,817 public pages.Information architecture

4. 04Rebuild Figma from the code

   So the values designers see never drift from the values users get, the Figma library was extracted back from the production tokens.

   →140 variables · 28 styles · 23 components (v1.0, 2026-09-17).Figma file

5. 05The day twelve features shipped at once, the numbers fell – six causes found and fixed

   Right after twelve features went live on August 27, the bounce rate went from 24% to 62%, time on site from 226s to 40s, and 36 rage clicks appeared – the only day in the whole observation window with any. The problem was the screens, not the features.

   →After fixing six causes: 0 rage clicks on August 29; on September 1 the bounce rate went from 70% to 29% and time on site from 36s to 115s.Usage

6. 06Don't show forecast prices beyond two years

   One-year outlooks ranked with an information coefficient of 0.19, positive in 93% of quarters; beyond two years it was 0.01 at the complex level. A number that can't be right isn't information.

   →Long-range forecasts show no prices – only the region level that held up (IC 0.16).

7. 07A missing value is 'not applicable', not zero

   Jeju and Ulleung have no motorways. Filling their 1,047 complexes with zero would read on screen as poor transport. When the validation window moved, indicators whose sign flipped were dropped for the same reason.

   →Station access is the baseline, with motorways and airports added for how people travel outside the capital; where a measure doesn't apply, it is left empty. A number that appears by chance and reads like evidence is the bigger risk.

8. 08Give AI the unit and meaning before the value

   With the MCP server open through seven read-only tools, a model read prices stored in units of ₩10,000 as won – a 10,000× error. A person asks when something looks off; a model makes something up.

   →A describe_fields tool now gives the model each field's unit and meaning before it reads any value.

Design

Information architecture

Three layout shells carry the same screens: a docked panel on desktop, a full-screen view on phones, and standalone routes for search engines.

Design system

The Figma library was rebuilt from production code. Below is the Figma file itself; under it, the same tokens rebuilt as React components.

CoverColorTypographyButtonScreensToken Index

Open in Figma

Loading the Figma file

Build

Build log

Selected milestones out of 2,380 commits. Each one is a decision that shipped.

1. 01

   Jul 1, 2026Foundation

   Engine and frontend in one push

   Set up the data engine and a Next.js + Tailwind frontend — the skeleton of a real estate terminal.

   commit 6e14935

2. 02

   Jul 7, 2026Brand

   Logo and identity

   Applied the wordmark, mark, and mobile logo across header and footer.

   commit a0d3448

3. 03

   Jul 16, 2026Design system

   Pulling UI into shared components

   Built Badge, Popover, and StatRow primitives plus spacing and state tokens, so hierarchy stopped drifting between screens.

   commit acdc364

4. 04

   Jul 19, 2026Search

   Natural language search, redesigned

   Separated names from conditions and added a concept lexicon, so every screener filter can be set in plain words.

   commit dad8b17

5. 05

   Jul 22, 2026Measure

   GA4 and Clarity

   The point where real usage data started coming in.

   commit 334d2b2

6. 06

   Jul 27, 2026Operate

   Deploy verification gate

   Detects missing JS chunks after each deploy and redeploys automatically.

   commit b0a958d

7. 07

   Aug 6, 2026AI

   Reevl AI as its own app

   Browsing and asking are different mental models, so the AI moved into its own /ai shell.

   commit 07296ee

8. 08

   Sep 11, 2026Performance

   First screen stops waiting on 7.8 MB

   Fixed endless loading on slow phones by serving a lightweight table first.

   commit db211f3

9. 09

   Sep 17, 2026Design system

   From code back to Figma

   Rebuilt the Figma design system from code: 140 variables and 23 components extracted from production.

   commit 9d2f5a2

Activity

›Stack and infrastructure

Next.js, TypeScript, and Tailwind on the front, with TradingView Lightweight Charts for time series. Behind it, a Python data engine. Hosting runs on Cloudflare Workers with D1 and R2, migrated from Vercel on July 25.

The same data is also exposed as a public MCP server so AI tools can query Korean apartment data directly.

Ship · results

Live product

SafariFileEditViewHistoryBookmarksWindowHelp

Fri Sep 18 9:41 AM

9:41 Fri Sep 18100%

9:41

Usage

5,000+

Monthly active users

Jul 2026

Launched

64,817

Public pages

Traffic sources

Measured in GA4 and Clarity, as of September 6, 2026. The assumption that "Korean real estate search happens on Naver" held up in numbers.

1,122

Visits from Naver (24× Google's 46)

912

Weekly users (up from 60)

42

Visits from AI assistants (ChatGPT)

›Sessions by channel, and search visibility

GA4 channels: Organic Search 1,199 · Direct 656 · Organic Social 82 · Unassigned 66 · AI Assistant 42 · Referral 16.

The sitemap lists 65,501 URLs. There was also an incident where Google's crawl dropped from 29,514 to 22 requests a day (the cause: detail pages not rendered on the server); after the fix, Google visibility is still recovering.

AI crawlers were slowed down, not blocked. Over 23 hours GPTBot made 34,856 requests (28%) and ClaudeBot 25,161 (21%) – far more than Googlebot's 480 – but a crawl-delay instead of a block kept the chance of being cited by AI. The 42 visits from AI assistants came from that.

Next – ON THE WAY

Site visits start only when you arrive, yet the neighbourhoods and roads you pass on the way are already part of the area. Splitting a visit into nine steps showed that half of its 14.3 hours went to travel and sorting notes. So my graduation exhibition, “REEVL: ON THE WAY”, turns the drive into exploration: Reevl's transaction and indicator data, redesigned for the car, attaches prices to the places you pass, and asking a question changes the route rather than returning an answer. It targets Pleos Connect on AAOS, testing whether exploration works within the visual limits of driving.

Where a person steps in

The operation runs by itself; what needs judgement comes to a person.

• By itself – transaction refreshes, publishing and error watching run as n8n workflows. Not a window to open every morning, but something that speaks up when it should.
• By hand – data from unreliable sources is refreshed manually, and the screen carries the date it is good for. Saying when something is from beats showing it as if it were current.
• Why it changed – the pipeline was green while publishing had been stopped for six weeks, and 11,891 server errors were reported as zero. Since then what is watched is the output, not the success log.

Reflection

A green pipeline doesn't mean the screen is right. Naver blog publishing had silently stopped for six weeks while its runs showed green, and a monitoring filter bug reported 11,891 server errors as zero. Since then twenty operational checks look at the output itself rather than success logs, and eleven build gates – including design-system conformance and a 432 KB first-screen JavaScript budget – block any deploy that fails one.

Crawlers are users too. One SEO tool's crawler was using 90.9% of the server's CPU. Growing visibility comes with an infrastructure bill – so now the first question is whether a metric actually matters to the product.

Still open. A 19.6% quick-back rate, Google visibility that is still recovering, and – because I built it alone – no evidence yet of how I collaborate.