Web platforms that turn messy data into a product people can search
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.
Fifteen hundred messy rows become a catalog people can search.
Run the ingestion, then search and filter 1,200 clean listings. The duplicates collapse, and the result count and timing under the list are measured on your device as you type — the same pipeline we build for marketplaces and aggregators.
Ingestion
Discovery
From listings scattered everywhere to a catalog that sells.
The same story we ship for every marketplace and aggregator — in four steps.
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 The same listing posted three times, half of them out of date.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.
We pull it into one clean catalog
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 catalog you can actually stand behind.
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.
More enquiries, a catalog 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.
The engineering, in plain terms.
Ingestion that deduplicates
We build pipelines that pull from external and raw sources, normalize fields (currency conversion, bilingual titles), and dedupe on fuzzy keys — on the rental aggregator that turned ~1,500 raw rows into ~1,200 records you could publish without checking them by hand.
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.
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.
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.
From kickoff to launch.
- 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
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
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
Harden and launch
We add moderation, tests, and a pre-commit quality gate, then deploy to a scalable serverless setup ready for real traffic.
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 stay fast at scale
- You have a two-sided or user-generated catalog that needs moderation to stay trustworthy
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.