Feed your RAG pipeline clean web data

Turn any website into clean, chunk-ready markdown, so your chatbot answers from real, current content instead of guesses.

The problem

Bad context, bad answers.

Your chatbot is only as good as its context. Copying pages by hand doesn’t scale, and raw HTML is full of menus, ads and scripts that burn tokens and confuse retrieval.

Raw HTML

help.example.com

Home · Pricing · Login

menu

50% off — buy now!

ad

Plans renew monthly…

the answer

tracking.js loaded

script

94% noise goes in

Chatbot

When do plans renew?

I can’t find that.

wrong answer

How Pline helps

One site in, clean context out

One site in, clean context out

Point Pline at a site. Map finds every page, Crawl pulls them all as clean markdown. Chunk it, embed it, and your LLM answers from real, current content, not guesses.

help.example.com

412 pages

messy HTML

Map

Crawl

Clean

markdown

.md

.md

.md

412 pages

ready to chunk

No HTML noise — fewer wasted tokens

No HTML noise — fewer wasted tokens

Whole sites in one job, not page by page

Whole sites in one job, not page by page

Protected sites handled automatically

Protected sites handled automatically

Re-crawl anytime to keep your index fresh

Re-crawl anytime to keep your index fresh

How it flows

From website to vector DB

01

Website

Docs, help center, blog

02

Map

Find every URL on the site

03

Crawl

Pull all pages as markdown

04

Chunk + embed

Your splitter & model

05

Vector DB

Ready for retrieval

01

Website

Docs, help center, blog

02

Map

Find every URL on the site

03

Crawl

Pull all pages as markdown

04

Chunk + embed

Your splitter & model

05

Vector DB

Ready for retrieval

Ready to power your AI products with clean, real-time data?