Service · 01

Web platforms that turn messy data into product

We build data-heavy web products — marketplaces, aggregators, and map-driven discovery tools — where the hard part is ingesting thousands of records, cleaning them, and making them instantly searchable. The result is a fast, scalable product where users find what they want in seconds and you can trust every listing in the database.

Next.js 16DrizzlePostgreSQLMapLibre
Catalogue & search

Fifteen hundred messy rows become a catalogue people can search.

Run the ingestion, then search and filter 1,200 clean listings. Watch the duplicates collapse and the result count update in under a millisecond — the same pipeline we build for marketplaces and aggregators.

Live · runs in your browser

Ingestion

1,500
raw rows
clean listings
House on Le Quang Daoagency-xls
1 BR on Vo Nguyen Giapold-site
House on Tran Bach Dangwalk-in
Studio on Nguyen Van Thoai facebook

Discovery

Villa on Ho Xuan HuongHai Chau · Villa · 4$1364
3-BR on Tran Bach DangThanh Khe · 3-BR · 4.1$1327
3-BR on Vo Nguyen GiapNgu Hanh Son · 3-BR · 4.1$355
3-BR on Phan TuHai Chau · 3-BR · 3.5$1580
1,200 listings ready to search/rentals
/00How it helps your business

From listings scattered everywhere to a catalogue that sells.

The same story we ship for every marketplace and aggregator — in four steps.

01 / 04

Your offers live in five different places

Spreadsheets, chat groups, a PDF, an old site. The same listing posted three times, half of them out of date. Customers give up before they find what they want — and you never even see the sale you lost.

duplicate
duplicate
SpreadsheetChat groupPDFOld site
rooms near the beach
under $4002 bedssea view
enquiries
every listing verified
02 / 04

We pull it into one clean catalogue

Every source flows into a single place, gets cleaned, and the duplicates collapse into one record you can trust. A pile of messy rows becomes a catalogue you can actually stand behind.

1,5001,200messy rows → clean listings
duplicate
duplicate
SpreadsheetChat groupPDFOld site
rooms near the beach
under $4002 bedssea view
enquiries
every listing verified
03 / 04

Customers find the right one in seconds

Search, filters and a map that stay fast over thousands of listings. People type what they want, see it on the map, and land on the right result on the first try — on any device.

duplicate
duplicate
SpreadsheetChat groupPDFOld site
rooms near the beach
under $4002 bedssea view
enquiries
every listing verified
04 / 04

More enquiries, a catalogue you trust

Buyers reach you instead of bouncing, every listing is one you can vouch for, and the whole thing keeps working as you grow from hundreds to thousands of records.

1,200+live listings, search still instant
duplicate
duplicate
SpreadsheetChat groupPDFOld site
rooms near the beach
under $4002 bedssea view
enquiries
every listing verified
How we implement it

The engineering, in plain terms.

01

Ingestion that deduplicates

We build pipelines that pull from external and raw sources, normalize fields (currency conversion, bilingual titles), and dedupe so a thousand-plus listings collapse to clean, trustworthy records — not duplicates and junk.

02

Map discovery done right

MapLibre with client-side clustering and price pins, plus a haversine 'nearby' query in the database, so the map stays smooth at scale and 'show me what's around here' is a real feature, not a gimmick.

03

URL-synced advanced filtering

Every filter — price, category, location, full-text search — lives in the URL with instant-apply, so results are shareable, bookmarkable, and back-button-safe, backed by Postgres full-text and trigram indexes for speed.

04

Moderation and user content

User-submitted listings get drag-drop photo upload and a moderation queue before going live, so the catalog stays high-quality even as outside contributors add to it.

How it goes

From kickoff to launch.

  1. 1

    Model the data

    We start from the real records you'll aggregate and design the schema and ingestion shape around them, so the data layer fits the actual sources from day one.

  2. 2

    Build the ingestion pipeline

    We wire up parsing, normalization, and deduplication, then validate the clean output against the raw input so you can see exactly what survived and why.

  3. 3

    Layer search, map, and filters

    We add full-text and geo search, the clustered map, and URL-synced filtering as one connected discovery experience rather than bolted-on parts.

  4. 4

    Harden and launch

    We add moderation, tests, and a pre-commit quality gate, then deploy to a scalable serverless setup ready for real traffic.

What you get

Deliverables, and when it fits.

Deliverables

  • A production Next.js 16 web platform deployed and ready for traffic
  • An ingestion pipeline that turns raw external sources into clean, deduplicated records
  • Map-driven discovery with clustering, price pins, and nearby-search
  • URL-synced advanced filtering with full-text and geo search
  • A moderation workflow for user-submitted content with photo upload
  • A test suite and pre-commit gate (typecheck, lint, tests, end-to-end) you can audit

A good fit when

  • You're aggregating listings, inventory, or offers from many fragmented or low-quality sources
  • Location matters — users need to search and discover on a map
  • You expect thousands of records and need search and filtering that stays fast at scale
  • You have a two-sided or user-generated catalog that needs moderation to stay trustworthy
Proof — shipped, not slideware

Shipped a bilingual rental aggregator that parsed roughly 1,500 raw listings down to ~1,200 clean, deduplicated apartments with map clustering and nearby-search, behind a test suite at 96% statement coverage.

Want this for your product?

Tell us the goal — we scope it honestly.

Start a project