Web Scraping & Data Extraction

Overview

What we deliver

We build reliable web scrapers and data extraction systems that collect, clean, and deliver structured data from public sources at scale.

We design and operate custom web scraping systems that pull structured data from websites, directories, marketplaces, and public sources. Our team handles the full pipeline, from target analysis and crawler development to proxy rotation, captcha handling, parsing, and delivery into your database, spreadsheet, or API. We write scrapers in Python, Node.js, and headless browser frameworks, and we account for rate limits, site changes, and legal constraints. Every job includes data validation, deduplication, and scheduled runs so the output stays fresh. We work with B2B teams that need lead lists, price monitoring, product catalogs, research datasets, and competitor intelligence. Deliverables come as CSV, JSON, database dumps, or live API feeds, with documentation that explains the source, frequency, and field mapping. We also maintain scrapers over time, fixing breakages and adjusting selectors as target sites evolve.

Fit Check

Built for teams like yours

Who it's for

Market research firms
Lead generation teams
E-commerce price monitors
Competitive intelligence analysts
SaaS product teams

Pain points we solve

Manual data collection consumes hours each week
Existing scrapers break when sites change
No structured pipeline for recurring extraction
Captchas and IP blocks stop large jobs
Raw data needs cleaning before use

What's included

Capabilities

Everything we cover in this engagement.

Custom scraper development
Headless browser automation
Proxy and IP rotation setup
Captcha solving integration
Data parsing and cleaning
Scheduled job orchestration
Database and API delivery
Ongoing scraper maintenance

How we work

Our process

A clear, predictable path from kickoff to outcomes.

01

Source audit

We review target sites, fields, and volume.

02

Scoping

We agree on schema, frequency, and delivery format.

03

Build

We develop and test scrapers in a staging environment.

04

Deploy

We run production crawls with monitoring and alerts.

05

Maintain

We fix breakages and extend coverage on request.

What you get

Deliverables & outcomes

What you get

Working scraper code
Cleaned dataset files
API or database endpoint
Job scheduler configuration
Field mapping document
Maintenance runbook

Outcomes you can expect

Fresh data available on schedule
Hours saved on manual collection
Higher coverage of target sources
Reliable input for downstream tools
Clear audit trail of extractions

Timeline

One to four weeks per scraper

Engagement

Monthly retainer, Project, Sprint

Tools we use

Python, Scrapy, Playwright, Puppeteer, BeautifulSoup

KPIs we track

Records extracted, Success rate, Run duration, Error rate, Data freshness

Client stories

What clients say

"

Our LCP was 4.8 seconds and Google was punishing us for it. They audited the build, dumped two plugins we did not need, moved hero images to a real CDN, and rewrote the critical CSS. LCP came down to 1.6 seconds within three weeks. Bounce rate on the pricing page dropped by a quarter without us touching the copy.

Sarah K.

"

Our SDRs were spending two hours a day copying lead data between Salesforce, Outreach, and a Google Sheet nobody owned. They mapped the whole flow, stitched it together in n8n, and added a dedupe step we did not even know we needed. Got 38 hours a week back across the team. The SDRs were the ones who pushed to expand it further.

Rebecca F.

Proof