Data Engineering
Web Scraping Services That Keep Running After Launch
We build and run web scraping services for companies whose product or pricing depends on fresh web data. Right now our team operates 370+ scrapers for a single client and keeps them working as the sites change. You get clean, structured data in your database or through an API.
Writing a scraper takes a few days. Then the source gets a redesign or a stricter bot check, and somebody has to notice by morning. That somebody is us.
Dmytro SerebrychCo-founder
Updated · Based on scraping operations we run in production
Founded in 2023 in Ukraine, 50+ engineers, clients across the US and Western Europe. One client review on our site sums up the scraping side: “Hands down best web scraping resources I’ve ever worked with.”
What Our Web Data Scraping Services Cover
A web scraper service is the visible part of the work. Most of the budget goes into what keeps the data accurate a year later.
Custom Scrapers And Crawlers
Collectors written for your specific sources in Python and Scrapy. We reach for a headless browser only when a site truly needs one, because lighter scrapers mean smaller server bills.
Managed Scraping Operations
We own the fleet after launch, from fixing broken selectors to adding sources when you need more coverage. For LiveTrend that means 370+ scrapers looked after by three engineers.
Proxy And Anti-Bot Layer
IP rotation and session handling, with the proxy budget set source by source. Protected sites get a heavier setup, and simple ones don’t pay for it.
Cleaning And Matching
We deduplicate, normalize currencies and units, and match the same product across stores. Raw HTML is never what we hand over.
Data Delivery
Straight into your PostgreSQL, as scheduled exports to a cloud bucket, or through a web scraping service API your developers call like any internal service.
Monitoring And Alerts
Every source has health checks on row counts and empty fields. When a site changes its layout, we see it on our dashboard before you notice a gap in a report.
Scraping As A Service, A Scraper API, Or Your Own Team?
Companies buy web data in a few different ways, and each one fails in its own place. Pick by who will fix the parsers when a source changes, because that is where the real cost sits.
| Option | Works well when | Breaks down when | Who fixes parsers |
|---|---|---|---|
| Online web scraping service (point-and-click tool) | A few simple pages, an export now and then | Sources run into dozens or sit behind bot checks | You |
| Scraper API or proxy vendor | You have engineers and only need infrastructure | Parsers break faster than your team can patch them | You |
| Managed web scraping as a service | The data feeds a product or daily decisions | You need one CSV, once | Us |
Scraper as a service sounds like a switch you flip. In practice it is a small team plus infrastructure, and the useful question is who answers the morning a retailer ships a redesign. If one of the first two rows fits your case, use it. We say this on first calls, and yes, it loses us some small projects.
What Companies Hire Us To Collect
Most of our data scraping services sit in retail and market intelligence, where prices and assortments change daily.
Product Catalogs
Product data scraping across retailers and marketplaces: titles, attributes, images and availability, matched to your own catalog.
Prices And Promotions
Competitor prices and active promos collected every day. This price intelligence is the core of the Retail Shake platform we work on.
Job Offers And Leads
Vacancies and recruiter contacts pulled from several job sources into one deduplicated queue, as in StaffPower Tools.
Local Business Data
Teams that want to scrape Google business listings for a local market usually get further with Google’s official Places API. We build on the route that holds up both legally and technically.
Alternative Data
Signals like hiring activity or product launches, collected for investment research. Alternative data web scraping only pays off with a long, consistent history, so we design for continuity before speed.
Mobile Apps
Some prices and listings exist only inside apps. Mobile app scraping services work with app traffic instead of web pages.
Industries We Collect For
Retail And E-commerce
Price position against competitors and marketplaces, active promotions and stock signals. Commercial teams at Retail Shake’s clients use this data to make daily pricing calls.
Fashion
Assortments and new arrivals across hundreds of brand and retailer sites. Category structures shift every season, which is why LiveTrend’s fleet needs constant upkeep.
Recruitment
Fresh vacancies with the recruiter contact attached. A job lead loses value within days, so StaffPower Tools collects on a tight schedule and alerts the team on every match.
What Web Scraping Costs With Us
We don’t price by the page or by the record. You pay for engineering time, and how much time a project needs depends on your sources far more than on how many rows you want.
| Role | Project work | Dedicated, long-term |
|---|---|---|
| Backend developer (Python, Scrapy) | $25–$35/h | $20/h |
| Data engineer | $25–$40/h | $25/h |
| Full-stack developer (dashboards, admin) | $30–$40/h | $24/h |
| QA engineer | $20/h | $20/h |
| Project management | Included | Included |
For scale: one dedicated backend engineer at $20 an hour comes to roughly $3,400 a month full-time. Proxy traffic and servers are a separate line from engineering hours, and on heavily protected sources they can rival the payroll.
What Pushes A Scraping Budget Up
- Protected sources. A site behind an active bot check has to be rendered in a full browser. That costs far more compute per page and breaks more often.
- Change rate. Fashion retailers reshuffle categories every season, and every reshuffle is a fix.
- Frequency. Hourly prices cost more to run than a weekly crawl of the same pages.
- Matching. Linking one product across 40 stores is often harder than scraping it in the first place.
Bot protection got noticeably stricter in 2026. We wrote up what that does to timelines in our guide to web scraping for business.
Scraping Operations We Run Today
Three published projects, from a 370-scraper fleet to a single-developer internal tool.
LiveTrend · Fashion intelligence, Franceproxy costs−67%
LiveTrend forecasts fashion trends from market data, and we run its whole collection side, from the 370+ scrapers to crawl monitoring and the proxy layer underneath. The team is three scraping engineers and one data engineer. On that operation proxy costs dropped 67% and crawls run 15% faster. Coverage grew by 56 new brands in three months. Read the case study →
Retail Shake · Retail intelligence, Franceengagementongoing
A competitive price monitoring platform for retailers and brands. Our engineers develop the product, and three data scraping engineers keep collection running for competitor prices and promotions, along with stock levels and product data. Read the case study →
StaffPower Tools · Recruitment, Poland and Romaniateam1 developer
An internal tool for a recruitment agency. It pulls job offers from several sources into one workspace and alerts recruiters when a matching vacancy appears. One full-stack developer built it and keeps improving it, which is about the right size for a focused internal tool. Read the case study →
How A Scraping Project Runs
Whether you need a website scraping service for three sources or web scraper services for three hundred, the order of work stays the same.
Source Audit
We look at how each source renders and what protection it runs. We also read its terms and check for an official API or feed. You get the list sorted by effort, with sources we’d advise against flagged separately.
Data Spec
What to collect, how often, and how we judge the data as correct all go into a spec in Notion. About half of it is written before the build starts. The rest fills in as we go.
Pilot On A Few Sources
A working pipeline on a handful of representative sources, so you see real data before paying for fifty.
Scale And Harden
We add the remaining sources, then tune proxies and retries. Sprints last one or two weeks and end with a demo plus a short written summary.
Operate
You get a written status in Slack every day, and fixes land as sources change. Our own tracker shows hours against your budget, so you never have to ask for a report.
How To Compare Web Scraping Companies
Search for web scraping companies and you land on two kinds of vendor. Data mining firms and dataset resellers sell ready-made data. A web scraping company like ours builds collection around your sources. What web scraping services companies actually deliver varies a lot more than their landing pages suggest, so test the shortlist the same way.
Here are the four questions we’d put to any web scraping service provider, us included:
- How many scrapers do you maintain today, and for how long? A demo proves little. Ask about a live operation and its age.
- What happens when a source breaks? Listen for monitoring and a response time. “We’ll fix it” is not a process.
- Who owns the code and the data? With us, you do. It’s written into the contract.
- Which sources would you refuse to collect? A data scraping company without an answer hasn’t thought about legal risk.
Good web scraping service providers answer all four without stalling. If a web scraping services provider can’t show you live monitoring, assume nobody watches it. The same check works for web data mining services sold as a subscription: ask how the data is collected and how often it refreshes. Most web data mining companies will tell you when asked directly. The ones that dodge the question have answered it.
Comparing data scraping companies on price alone rarely works. A website scraping company that quotes half of everyone else has usually left maintenance out of the quote. In our experience that is the surprise people dealing with website scraping companies hit around month three.
The Legal Ground Rules We Work By
We collect publicly available data. During the audit we check each source’s terms and robots rules, and we don’t collect data behind logins or paywalls without the owner’s permission. Personal data needs a lawful basis under GDPR or local law, so we raise it before the build, not after. When an official API exists, we usually recommend it first. This is our practice, not legal advice, and for sensitive sources your lawyer should see the plan.
Proxy Services For Scraping: Part Of The Pipeline
We don’t resell proxy services for scraping. The proxy layer is something we design and tune inside the pipeline you pay us to build.
Picking a proxy service for scraping per source matters more than picking the biggest vendor. Datacenter IPs handle unprotected sites at a fraction of what residential traffic costs. Paying residential rates for every request is an easy way to overspend. LiveTrend’s proxy layer was built with cost in mind from the start, and its proxy bill is 67% lower for it.
The Stack Behind Enterprise Web Scraping
Enterprise web scraping is mostly an infrastructure problem. Hundreds of scrapers have to run on schedule and write into one clean store, which is what this stack is for:
Collection
PythonScrapyNode.js
APIs
FastAPINestJS
Storage
PostgreSQLRedis
Infrastructure
DockerKubernetesAWSAzureGoogle Cloud
Web scraping solutions that feed AI models need the same pipeline plus a retrieval layer on top. Our AI development cost guide covers what that adds. If you’d rather have scraping engineers inside your own team, see dedicated developers.
Frequently Asked Questions
Engineering is billed by the hour: $25–$35 for a backend developer on project work, $20 in a long-term dedicated setup. A pipeline for a few unprotected sources is a short project. A fleet of hundreds of scrapers is a monthly team. Proxies and servers come on top, and protected sources push both up.
Often, yes, but it depends on the source. A site’s terms and copyright still apply, and GDPR matters for anything about people. We review each source before collecting and flag the risky ones. For high-stakes data, ask your lawyer.
We sign an NDA before the project starts, and client data is stored encrypted. If you have your own security requirements, send them with the source list and we’ll build to them.
Mostly in wording. “Data scraping” is the wider term and can include files and app data, while web scraping means websites. People search for webscraping services and web scraping services alike. Same work.
A team starts within 3–7 days of a signed scope. We usually begin with a pilot on a few representative sources, so you see real data in the first weeks.
The data arrives through an API, a database or files, depending on what your systems expect. The code and IP belong to you under the contract either way, so you can move the operation in-house later if you want to.