Web Scraping & Data Extraction Services
Web scraping services that survives the things that break most scrapers
A managed web scraping and data extraction service for teams that need the data to keep arriving after a site changes its layout, adds a login wall, or ships a redesign. We build, run, and repair the pipeline. You get clean data on a schedule.
Crawlify powers ScholarMeet’s data pipeline, continuously aggregating verified conference data from hundreds of academic websites.
Why scrapers break
Most scrapers don’t fail in one dramatic block. They fail slowly, for the same reasons every time: a site redesign, a renamed CSS class, a new cookie banner, a field that quietly moves. That maintenance is the real cost of web data, and it’s the part we take off your plate.
Layout and DOM changes
A redesign renames a class or moves a field, and every selector pointing at it stops returning the right value. Nothing errors. The data just goes wrong.
Anti-bot and login walls
A site adds bot detection, a cookie banner, or a login gate. The scraper that worked yesterday now collects an interstitial page instead of your data.
Scale that compounds it
One source is manageable. Dozens to thousands of sources means something is always changing, and the maintenance never lands on a quiet week.
What we handle
We build for the sources that actually break scrapers, not just the easy ones.
Marketplaces and listing sites
Pagination, filters, and category trees that change structure without notice.
Review and ratings pages
High-churn content where yesterday’s extraction is already out of date.
Directories and search results
Deep result sets where completeness matters as much as accuracy.
JavaScript-heavy sites
Content rendered client-side, where a plain HTTP fetch returns an empty shell.
Sites with anti-bot protection
Bot detection and login walls, handled as a design constraint rather than a blocker.
Structured and semi-structured sources
Where the shape of the data matters more than the shape of the page.
How our pipeline is different
We run web data collection the way we run production software: version-controlled, tested, monitored, and repaired. The difference shows up in numbers, not adjectives.
60 of 62
workflows recovered on their own in a kill drill
$0.0041
to re-run 14 of 41 nodes in a targeted repair
$0.004–$0.12
per source, vs $2.40–$6 for free-running agents
1,600+
eval tests run against the pipeline
Human review is part of how we check the data. Most managed providers do this, so we treat it as standard, not a headline. What’s different is that our failure and repair costs are measured and auditable, where most of the market offers a round-number guarantee.
Three ways to get this data
You have three real options. Here’s the honest comparison.
| DIY scraper or scraping API | Free-running AI agent | Xillentech managed pipeline | |
|---|---|---|---|
| When a site changes | You find out when the data stops, and you fix it yourself | Breaks silently, often unnoticed | Repairs itself. 60 of 62 recovered on their own in a kill drill |
| Cost per source | Hidden in your team’s time | $2.40–$6 | $0.004–$0.12 |
| Recovering from a crash | Manual restart | Starts over from zero | Resumes where it left off |
| Data checking | You build it yourself | Rarely built in | Built in, human-reviewed |
| What you’re left with | Code your team must maintain | Nothing durable | Clean structured data, delivered |
“Crawlify powers the data pipeline behind ScholarMeet. We needed to aggregate conference data from hundreds of scattered academic event websites: speaker lists, submission deadlines, topics, venues, and deliver it as a clean, structured feed. What would have taken our team weeks of manual work now runs continuously with verified accuracy.”
ScholarMeet.com — Academic Conference Management Platform
How it works
Four steps from your source list to data landing in your stack on a schedule.
1
Send us your sources
Tell us the sites and the fields you need. No commitment at this stage.
2
Get a free sample
We scope it and send back real data in your format, before you commit to anything.
3
We build and test it
Every pipeline runs against gold-standard tests before it goes live.
4
It keeps running
Self-healing repair kicks in when a site changes, and we monitor it going forward.
See a sample of your data first
A free data sample is a normal first step in this market, and it’s the fastest way to judge fit. Tell us the sites and the fields you need. We’ll send back a real sample in your format. No pipeline gets built until you’ve seen the data.
Why teams trust us with their data
We’re a senior studio, not a large offshore team working through junior hands. About 20 people, most of them writing the pipelines themselves.
15+
years in production software
315+
projects delivered
98%
client retention
4.9/5
client rating
Frequently Asked Questions
What is a managed web scraping service?
A provider builds, runs, monitors, and repairs the whole data pipeline for you. You define the sites and fields; you receive clean, structured data on a schedule instead of maintaining scrapers yourself.
How is this different from a scraping API?
A scraping API hands you the tools and you still write, run, and fix the extraction. A managed service owns the outcome end to end, including repairs when a site changes. With an API, a site redesign becomes your engineering ticket. With a managed pipeline, it becomes ours.
Why do web scrapers break?
Sites change. Layouts get redesigned, CSS classes get renamed, login walls appear, fields move. A scraper built for yesterday’s page stops returning correct data, and often does so without throwing an error, which is what makes it dangerous. The data keeps flowing, it’s just wrong.
Is web scraping legal?
Scraping publicly available data is generally lawful in the US, established by cases like hiQ v. LinkedIn, but the details matter. We respect robots.txt and each site’s terms, avoid personal or gated data without permission, and can talk through the specifics of your sources before we start.
What data formats do you deliver?
CSV, JSON, or straight into your warehouse. Tell us how your team consumes data and we match it, rather than handing you a format you then have to convert.
Can you handle sites with anti-bot protection?
Yes. That’s most of what breaks scrapers in the first place, and it’s what our pipeline is built to survive and repair itself around.
Can you run this on a schedule, not just once?
Yes. Most of our pipelines run on an ongoing schedule with monitoring and self-healing repair built in, not as a one-time job. A one-off extraction is a snapshot; most teams need the data to stay current.
Do you offer a free data sample?
Yes. Tell us the sites and fields; we scope it and send a real sample in your format before you commit. You should see the actual data before you decide whether it’s worth building a pipeline around.
Let’s make it survive its worst day.
Send us the sites and the fields. We’ll come back with a free sample and a plan to keep the data arriving.
Web data for competitor monitoring, pricing, and lead lists
Track competitor pricing and stock, monitor product listings across marketplaces, build prospect lists from directories, or check compliance across hundreds of sites we build the pipeline for your specific use case, not a generic scraper. You define the sites and fields we handle the extraction, the self-healing repairs, and the schedule.
