We build scrapers and parsers that collect data from websites, feeds and documents and hand it over clean: in a spreadsheet, your database, a CRM or a Telegram bot. The hard part is not the first run, it is the hundredth — when the site changes its layout, blocks the requests or lists the same item three times. That is what we build for, and the scope and price are fixed before we start.
A scraper is easy to write and hard to keep alive
A script that pulls one page works on the day it is written. In production a scraper meets portals that block repeated requests, layouts that change without notice, the same listing posted by three agencies, and prices that only matter when they move. So we design for those from the start: request pacing and rotation, alerts when a source stops returning data, deduplication, and a record of what changed and when.
What we build
- Listing and price monitoring — new items, price drops and stock changes across portals and online stores, with an alert when something you watch moves.
- Crawlers — walking a whole site or catalogue on a schedule and keeping your copy up to date.
- Data parsing — turning documents, feeds and messy exports (PDF, XML, CSV, HTML) into one table with one format.
- Delivery where you work — a spreadsheet, your database, a CRM, an API, or a Telegram bot with access control and an admin panel.
- AI where rules run out — reading unstructured text and documents, with a human check where the model is unsure. More on AI integrations.
Clean data, not a dump
Raw scraped data is full of copies and gaps. We merge duplicates (the same flat listed by several agencies, the same product under three names), normalise prices, dates and addresses into one format, and flag records that are missing what you need — before the data reaches you, not after.
Work in this area
- Real-estate listings bot (Poland). Collects new listings from a property portal, removes duplicates and tracks price drops; subscribers get them in Telegram, with per-seat access, an admin panel and statistics. Running every day for months.
- LinkedIn → ClickUp (Estonia). A browser extension that moves profile data from LinkedIn into a team's ClickUp workspace.
What we do not build
Scrapers that get around a site's protection to reach data it hides, collect personal contacts of people in the EU without a legal basis, or create fake accounts. If a source needs a login, an official API or a data agreement, we tell you so at the start — it decides whether the project is safe to run.
How it works
- Sources and fields: you show us the sites or files and what you need from them.
- A test run on a sample, so you see real data before committing.
- A fixed scope and price, including how often it runs and where the data goes.
- Build, launch and monitoring: we watch for broken sources and fix them under a support plan.
Questions about scraping projects
Is web scraping legal?
Collecting publicly available, non-personal data is generally fine; the line is crossed by bypassing protection, ignoring a site's terms where they bind you, or collecting personal data without a legal basis (GDPR in the EU). We check each source at the start and say plainly if one is a risk.
What happens when the website changes?
The scraper alerts us when a source stops returning data or returns it in a new shape, and under a support plan we fix it. Without one, a fix is billed by the hour.
Do I need proxies?
Only for sources that limit repeated requests. When they are needed, the proxy service is on your account and paid by you; we say what it costs before you decide.
How do I receive the data?
Wherever you already work: Google Sheets, your database, an API, a CRM, or a Telegram bot. You own the code and the data.
Tell us what data you need
The sources, the fields and how often. We come back with a test on a sample and a fixed price.
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