Secure web scraping at scale
Every automation runs on data, and the data has to come from somewhere. I build scraping infrastructure that keeps pulling it reliably, at scale, without getting blocked. So far it has held up past 10 million data points.
- Over 10,000,000 data points successfully processed
- Continuous data flow without blocks
- Direct integration into databases, dashboards, and automations
From process to result.
- 01
Process analysis & NDA
- 02
Solution design
- 03
Prototype in 7 days
- 04
Production & handover
Problem
The data you need sits behind anti-bot walls, rate limits, and pages that change without warning. Off-the-shelf tools give up at the first wall, and collecting it by hand was never going to scale.
Solution
I build dedicated pipelines with rotation, anti-bot bypass (Cloudflare and DataDome class), and real fault tolerance, so the data keeps flowing even when the source moves the goalposts.
How I approach it
Reliable scraping is an engineering job, not a quick script. I design each pipeline around the exact sources you need, with rotation and anti-bot handling built in from day one instead of bolted on after it breaks.
Everything is monitored and built to recover, so a changed source means a hiccup, not a dead pipeline. You get clean, structured data on a schedule you can build on, and it stays inside your legal and confidentiality lines.
What you get
Anti-bot bypass
Getting past Cloudflare and DataDome-class protection with behavior that looks like an ordinary visitor.
High-volume pipelines
Architecture proven past 10 million data points, built to recover on its own and run continuously.
Logistics specialization
Hands-on experience with tender, transport, and freight sources and the quirks that come with them.
Clean, structured output
Data lands normalized and ready for a database, a dashboard, or the next automation.
Frequently asked
Is scraping reliable on protected sites?
Yes. Each pipeline uses rotation and gets past Cloudflare- and DataDome-class protection, and it recovers on its own when a source changes.
What volume can you process?
The setup is proven past 10 million data points and built to scale further without falling over.
In what format do I get the data?
Normalized and structured, ready for a database, a dashboard, or straight into an automation.