Background
Arnold is a full-stack developer working across early-stage startup environments, and holds a First-Class BSc in Computing from Coventry University. He builds the DataFixr platform with a security-first, UX-led approach.
- BSc Computing, First-Class Honours, Coventry University
- Full-stack developer across early-stage startups
- Previously at eSIM Go
What Arnold Kocsis writes about
Arnold Kocsis writes the DataFixr guides covering security-first, ux polish, startup pace. They come out of that operating experience rather than from keyword research.
- Linkedin Data
- Data Extraction
- Web Scraping
- Crm Hygiene
- Rocketreach Alternative
- Prospecting
- Data Enrichment
- Data Operations
Where a guide covers a regulated area such as TPS screening or lawful basis for outreach, it describes the operational process and points to the primary source. It is not legal advice.
Guides by Arnold Kocsis
9 published guides.
LinkedIn Profile Data Extraction Fields: Education, Work History, About, and Headline
LinkedIn profile data extraction works best when the output is split into stable fields: name, headline, current company, work history, education, about text, source URL, and review status.
RocketReach Alternatives: Contact Search and the Data Operations Layer
Contact search answers who someone is and how to reach them. What happens next - cleaning, deduplication, enrichment, validation, governed exports - is a different job, and often a different tool.
From Raw LinkedIn Extract to CRM-Ready Records
Extracted is not the same as usable. The failure modes specific to LinkedIn profile data, and the cleanup that stands between a raw extract and a CRM record you can trust.
AI Token Saving for Data Extraction: Choosing an Extraction Architecture
Using AI for every step of data extraction is one of the fastest ways to inflate your API bill. This guide explains how to reduce AI token usage, extract data without LLMs, and keep AI where it actually earns its cost.
LinkedIn Data Extraction: A Faster Way to Collect Structured Lead and Profile Data
Manually copying LinkedIn data is slow and inconsistent. Fetchr extracts structured person and company data from LinkedIn automatically - name, title, company, location, contact info, and more - without manual copy-paste or AI token costs.
How to Scrape Websites Without Using AI Tokens: A Deterministic Approach
Deterministic extraction with no model in the loop: where the data actually sits in a page, how to target it so the template survives a redesign, and when this approach is the wrong tool.