Supaklin — text cleaning API for LLMs
Supaklin mascot — a friendly cleaning character representing text sanitization

Stop Feeding Your LLMs Scraped Garbage

Clean Web Text.
Instantly.

Surgically remove UI noise from scraped text. Keep every word that matters, discard everything that doesn't.

Instant
Blink and it's done.

Cleaning happens before your request even feels slow.

Save Tokens
On every call.

Less noise in = lower costs out. Your context window will thank you.

Text-Level
Works on raw text, not just HTML DOM.

Throw us anything. We'll make it LLM-ready.

Input Source0 tokens
Skip to main content LinkedIn Search Home My Network Jobs Messaging 5 Notifications 12 Me For Business Try Premium Free Start a post Photo Video Event Write article Sort by: Top Sarah Chen Data Engineer at ScaleML 2nd 3h Edited Just spent 2 days debugging why our LLM was hallucinating on product data. Turns out the web scraper was feeding it raw HTML with navigation menus, cookie banners, and footer links mixed into the actual content. Lesson learned: HTML to markdown conversion is not optional anymore. Clean data = better embeddings = fewer hallucinations. Anyone have recommendations for web scraping cleanup tools? Looking for something that can: - Strip boilerplate content - Convert to clean markdown - Handle dynamic JavaScript-rendered pages #WebScraping #DataPipelines #LLM #RAG #MachineLearning Like Comment Repost Send 847 156 comments Alex Rivera ML Engineer at Anthropic 2h This is exactly why we built a preprocessing layer before our RAG pipeline. Raw scraped data is basically unusable for context windows. Reply 23 Marcus Thompson Founder at CleanText API 1h Sarah - check out dedicated HTML cleaning APIs. They are designed specifically for LLM preprocessing. Way better than regex hacks. Reply 45 Add a comment... Messaging LinkedIn Corporation 2025 About Accessibility User Agreement Privacy Policy
Clean Output

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Built for AI Pipelines

Anywhere you feed web content into an LLM, Supaklin makes it better.

RAG Pipelines

Cleaner chunks mean better retrieval. Remove navigation and boilerplate before you embed, so your vector search returns relevant content instead of "Home | About | Contact" fragments.

Web Scraping

Scrapy, Playwright, Puppeteer all give you the full page. Supaklin strips it down to the content you actually wanted. No more regex-based cleanup scripts that break on every site.

LLM Context Optimization

Every token counts. A typical web page is 30-60% boilerplate. Removing that noise means you can fit more actual content in your context window and spend less on API calls.

Data Preprocessing

Building training datasets or fine-tuning corpora from web sources? Clean the data before it enters your pipeline. Consistent, noise-free text leads to better model outputs.

Frequently Asked Questions

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