Kai Watanabe
Scraping Infrastructure Evangelist
Kai Watanabe is a Scraping Infrastructure Evangelist at Nstdata, specializing in large-scale web scraping systems, anti-detection technologies, and proxy-powered data pipelines. He is passionate about helping businesses build resilient and efficient data collection infrastructures. His content focuses on scraping frameworks, automation strategies, IP management, and the evolving landscape of web intelligence.
All Articles
What Is an ISP Proxy? Static Residential Explained
Understand ISP and static residential proxies, how they differ from rotating residential traffic, use cases, and selection trade-offs.
IPRoyal Alternative: Flexible Residential Proxy Options
Compare IPRoyal and Nstdata residential proxy workflows by billing, identity behavior, collection, operations, and usable output.
Decodo (Smartproxy) Alternative: Nstdata Compared
Compare Decodo and Nstdata by proxy scope, collection layer, billing model, operations, and workflow fit.
ScrapingBee Alternative: Nstdata Crawl Compared
Compare ScrapingBee and Nstdata Crawl for HTML API calls, JavaScript rendering, site crawling, artifacts, and operations.
Crawl a Website with LangChain: Full Web Loader Tutorial
Learn how to crawl an authorized website with LangChain, convert validated pages into Documents, and build a refreshable web-data pipeline with Nstdata.
Residential vs Datacenter Proxies: Which Do You Need?
Residential and datacenter proxies differ most in network origin, target acceptance, performance consistency, and billing structure. This guide explains when each type works better and how to test both using cost per accepted result.
10 Best LinkedIn Profile Scrapers in 2026 [Don't Miss]
A ranked, verified look at 10 LinkedIn profile scrapers and enrichment tools for 2026 — browser automation, developer APIs, and contact databases — plus the current legal status of scraping LinkedIn and how to handle profile data responsibly under GDPR/CCPA.
How to Scrape LinkedIn Profiles in 2026: Step-by-Step Guide
Scrape public LinkedIn profile data with Python the compliant way: what's legal, what hiQ v. LinkedIn really decided, and working requests/BeautifulSoup code for name, headline, location, and current role — no login, no connections data, no bypassing LinkedIn's bot detection.
Is Firecrawl Too Expensive? Real Cost Per Page
Firecrawl's headline credit rate is not the same as cost per usable page. This guide calculates effective cost and compares the billing model with Nstdata Crawl.
