Protect your bottom line by cutting token waste by up to 66% and reducing model hallucinations. No code, no setup. Instant document optimisation that saves your business serious time and money.
Drop a file here or click to choose
Up to 25 MB free, 100 MB on Pro. We never store it.
Chat apps and APIs pull the text out and render every page as an image as well. Markdown keeps the headings, lists and tables. The packaging goes.
Measured with Anthropic's token counter on three real PDFs of 59, 92 and 160 pages.
Claude token counts via the Anthropic API, September 2026.
| Real file | Pages | PDF attached | Markdown | Tokens saved | Saved |
|---|---|---|---|---|---|
| Enterprise agreement | 59 | 142,365 | 47,482 | 94,883 | 67% |
| Industry report | 92 | 255,927 | 113,194 | 142,733 | 56% |
| Annual report | 160 | 378,660 | 143,054 | 235,606 | 62% |
| Total | 311 | 776,952 | 303,730 | 473,222 | 61% |
Absolute counts differ between tokenisers (OpenAI GPT and o-series, Gemini) but the compression ratio holds: the page images and layout noise removed are the same whichever model counts what's left.
Token savings on prompts are the entry point. Standardising your corporate data as Markdown is the baseline for any secure, scalable AI system built on your own documents.
You deploy chatbots that know your company policies instead of guessing at them. Feed a chatbot raw PDFs and it struggles to retrieve the right answer under load. Feed it clean Markdown and it searches structured data. Staff and clients get precise answers on HR guidelines, operations manuals and product specs, without the errors.
You build one central data hub any AI tool can read instantly. Most corporate file networks are landfills of unorganised PDFs, Word docs and local spreadsheets. Converting your primary resources into a Markdown repository cleans that footprint. Point any new AI tool at it and pull insights across decades of records.
You feed your AI clean context files without paying for thousands of engineering hours. Enterprises rarely train models from scratch. They load their own data into the model's working memory. Messy data in, messy output out. Markdown delivers noise-free, structured text that lets your model run specialised audits and analysis without fuss.
You build templates and documents that paste across every tool in your stack with zero formatting errors. Markdown is the layout standard those platforms use natively. Convert legacy files once and move large documents, tables and project outlines across your whole productivity stack with headings, links and bullets intact.
Files up to 100 MB. Every format. Nothing stored. Under $5 a month, cancel any time.
Get a year for $59Need a higher limit? Email [email protected] and we'll set one up.
Each format has its own page: what survives, what doesn't, and what to fix before you drop it in.
Three conversions are free, no account needed. Pro is a flat $59 USD a year for 300 conversions a month, which is 10 a day, every day.
Cancel any time and keep access to the end of your year. 14-day refund if it's not for you.
Need a higher limit for a team or a bulk job? Email [email protected].
Need a higher limit? [email protected]
A PDF attached to a prompt is charged twice: once for the words and once for an image of every page. On Claude the page image alone is about 1,500 tokens. Markdown carries the words and their structure (headings, lists, tables) and nothing else, so the image charge disappears and the layout noise goes with it. On the three files we measured, that cut the token bill by 56% to 67%. The saving repeats on every message, because the model re-reads the whole conversation each time you send.
A Markdown file is a plain-text document that uses simple keyboard symbols to say how text should be formatted. The files end in .md or .markdown. Created by John Gruber in 2004 as an easy-to-read alternative to HTML, it sits between a bare .txt file and a full Microsoft Word .docx.
No hidden code and no toolbar buttons. You style text with punctuation:
# This is a heading**bold text**[Google](https://google.com)Open a Markdown file and you're reading raw, human-readable text. Software called a Markdown processor (or parser) turns those symbols into a formatted web document (HTML) instantly.
| Aspect | Plain text (.txt) | Markdown (.md) | Rich text (.docx / Word) |
|---|---|---|---|
| Formatting | None | Visual styling via symbols | Fully styled |
| Human-readable raw | Yes | Yes | No (hidden XML code) |
| Compatibility | Universal | Universal | Requires specific software |
| File size | Extremely small | Extremely small | Large |
Converting messy source documents (PDF, DOCX, HTML) into clean Markdown before they reach an LLM is industry best practice. It strips design metadata, keeps the semantic layout (headings, tables) and cuts the character count, which cuts your token bill directly.
The unit you're billed in. Every AI plan and API meters usage in tokens: roughly three-quarters of an English word, and a lot less than that for tables and formatting code. Your monthly limit is a token limit. An attached file spends tokens before you've typed a question, and spends them again on every reply, because the model re-reads the whole conversation each time.
Every major Large Language Model (LLM) reads, understands and answers in Markdown natively. They're trained on internet text, documentation and code, so Markdown is their home language for structured text. The markdown from Save My Tokens pastes straight into any of these:
No. We don't want the risk of holding your documents, and you shouldn't have to carry it either.
Governance and risk were placed at the front of this build, not bolted on afterwards. Your file is converted in memory and released the moment the response reaches your browser. No copy is written to disk. No copy is retained. Nothing is available to us, or to anyone else, once the response is sent.
What we do keep is a count of conversions, so the free tier and the Pro cap work. That's the whole record. This position is set at director level by a graduate of the Australian Institute of Company Directors, and it's written into our Privacy Policy and Terms.
Same benefit, same reasons. Office files carry styling, embedded graphics, hidden sheets, comments, tracked changes and empty space the model would otherwise wade through. Converting to Markdown strips that noise and keeps the structure: headings, lists and tables arrive as real Markdown, slide decks read in order, and spreadsheets become clean grids the model reads cell by cell.
The meter shows the markdown token count for these files. The attached-versus-markdown comparison is measured on PDFs only, because that's where the page-image charge sits.
A scan with no text layer has nothing to extract. Run it through OCR first (Adobe, or your scanner's software) and then convert it. We'll flag it rather than pretend it saved you 99%.
14 days, email us. Nothing here limits your rights under Australian Consumer Law or the consumer law where you live.