Free knowledge base builder

How it works

1. 1

   Drop in a document

   PDF, Word, CSV, Markdown, HTML, or plain text. No account, no card, no email.

2. 2

   We clean and chunk it

   Page furniture and broken formatting come out. What is left gets split into retrieval-sized chunks with overlap.

3. 3

   Download and upload

   Plain .txt files with a token count on each one. Drop them into ChatGPT file chat or a Claude Project.

Why a cleaned, chunked file beats a raw export

Export a PDF and the headers, footers, page numbers, and broken column layouts all come through as text, mixed in with the real content. Cleaning strips that page furniture out, so what is left is the document itself.

Size matters just as much. One 200-page document is a single enormous blob. Split it into focused chunks, give each one a little overlap with its neighbours so an idea that spans a boundary appears in both, and label each chunk so you can see what it holds and how many tokens it is.

That is the whole job this tool does — and it is the step most PDF converters skip. They hand you one large Markdown file and leave the splitting to you. Here is how to think about chunk size and overlap if you want to tune it yourself.

What you get back

• ✓Plain .txt files — no proprietary format, nothing to convert again
• ✓An approximate token count on every chunk, so you know it fits before you upload
• ✓Source attribution on each chunk — you can always trace a passage back to its file
• ✓Overlap between neighbouring chunks so boundary-spanning ideas stay retrievable

Frequently asked questions

Is this really free?

Yes. One file up to 5MB per conversion, no account and no credit card. Packs start at $9 once if you need more files. Nothing on this page is gated.

Do you store my documents?

No. Word, CSV, TXT, Markdown, and HTML files are processed in your browser. PDFs are sent to our server only to extract their text layer, and the file is discarded as soon as the text is returned. Nothing is stored — no file is written to disk or a database.

What file formats can I use?

PDF, Word (DOCX), plain text, CSV, Markdown, and HTML. PDFs need a real text layer — if the page is a scanned image, there is no text to extract and you will need to run OCR on it first.

What do the output files look like?

You get plain .txt chunks. Each chunk carries a header with its number, the source file it came from, its key terms, and an approximate token count, so you know it fits before you upload it anywhere.

Why does chunking matter for ChatGPT or Claude?

Chunks keep each file a manageable size for upload and context limits, and every chunk is labeled with its source and an approximate token count, so you know exactly what you are giving the model.

How is this different from a PDF-to-Markdown converter?

Converters hand you one large file and stop. That is extraction, not preparation — you still have to split it yourself. This tool finishes the job: it cleans the text, splits it into retrieval-sized chunks with overlap, and labels each one with its token count.

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