Skip to content
Sırdaş

Your documents. Your agent. Your machine.

Give AI access to your private documents without forcing them into the cloud.

Try it now: PDF to Markdown for AI

Sent to servers: 0 BNothing left your device

21

tools, all inside your browser

0

bytes of your file sent anywhere

0

accounts to create

11 MB

of OCR engine, hosted right here

For AI agents

Give your agent Sırdaş.

Your agent reasons; Sırdaş hands it the documents. An MCP server that runs on your machine reads PDFs, scans, Word, Excel, email and photos, and gives the model what it needs, with the page every fact comes from.

claude mcp add sirdas -- npx -y @sirdaspdf/mcp@0.4.3

New in version 0.4.0 of the MCP server: build_context, to ask a whole folder and get only the context that is needed, with measured token counts. You can also try it on the web.

  • Reads any document in one call

    Unlocks it, runs local OCR on scans, identifies the type and extracts the key fields with their page and evidence.

  • Content is data, not orders

    Text a person cannot see (white, tiny, off the page) is flagged before the document. A PDF does not get to instruct your agent.

  • Only inside the folder you choose

    Every path is checked after resolving symlinks. Nothing is overwritten without overwrite: true, and there is a read-only mode.

What you can ask

  • “Read this invoice and give me the total and tax ID”
  • “Compare both versions of the contract”
  • “Redact this medical record before summarizing it”
  • “Turn the statement's table into CSV”

Almost any file goes in. What your AI already understands comes out.

We don't ask for trust. We give you proof.

Any cloud suite can promise to delete your file. We do something different: we never receive it, and you can check.

0 bytes leave your browser

Open the inspector (F12 → Network) while you process a file. No request carries your document, because there is no server to receive it.

Four ways to verify it
NetworkFetch/XHRJSDocREC
Name · Status · Type · Size

0 requests · 0 B transferred

while you process your file

Reversible redaction

IDs, names, emails and phones become consistent placeholders before they reach the AI. Paste the answer back and the real data returns. Nothing is destroyed.

Patient Juan Pérez, ID 1.020.345.678, tel 310 555 0199

Patient [NOMBRE_1], ID [DOCUMENTO_1], tel [TELEFONO_1]

Restore the real data

Works offline

Turn off WiFi and keep working. If your file were uploaded anywhere, this would be impossible.

Enforced by the browser, not by our word

The site ships a CSP header that blocks the code's connections (fetch, XHR, WebSocket, beacons) to any other domain. You can see it in DevTools.

Content-Security-Policy: connect-src 'self'

The same engine, for your agents

MCP server, CLI, Python and n8n run on your machine. Claude Code or Cursor read your documents without them leaving it.

claude mcp add sirdas -- npx -y @sirdaspdf/mcp@0.4.3For developers

Free for people

No size limits, no watermarks, no account.

For business

Three gestures. No round trip.

  1. 01

    Drop the file. It opens in your browser's memory.

  2. 02

    Choose what to do. The work runs on your processor.

  3. 03

    Download the result. Close the tab and nothing remains.

Pick your tool

Each one opens straight away. No queue, no sign-up, no daily limit.

For AI

Optimize

Organize

Edit

Security

Convert

New niche

Train your model on your documents. Without them leaving your machine.

Drop a folder of PDFs and get a JSONL ready to fine-tune a model or feed your RAG: redacted, deduplicated and split by document. It is the chain no cloud parser can offer with client documents.

  1. PDF
  2. Markdown
  3. Redact
  4. Dedupe
  5. Split
  6. JSONL
  • Split by document

    Never by chunk. Otherwise the model already saw the template and the metric lies.

  • MinHash + LSH deduplication

    Repeated text gets memorized instead of learned. Threshold 0.8, verified with exact Jaccard.

  • Personal data out, and reversible

    A model repeats what it sees. Redaction is on by default and the mapping stays with you.

Out in the format your trainer expects

  • JSONL · chat (TRL, OpenAI)
  • prompt / completion
  • Alpaca
  • ShareGPT
  • LangChain Documents
  • LlamaIndex TextNodes
  • Embeddings
  • train / validation / test

What happens to your file

Cloud suites promise to delete it within an hour or two. Here there is nothing to delete.

ToolUploads your file?How long do they keep it?Works offline?
Cloud suites, web version (iLovePDF, PDF24, Smallpdf)Yes, to their serversBetween 1 and 2 hours, per each policyNo
SırdaşNo. It never leaves your browserNothing to keepYes

Source: each service's public privacy policy, reviewed in September 2026. The table compares their web versions: iLovePDF Desktop, PDF24 Creator and the Smallpdf Windows app process on the device, but have to be installed.

What we learned, with the sources in plain sight

Articles on preparing documents for AI without handing them to anyone. With citations, with what does not work, and with what we still cannot do.

Read the blog

Your documents tell your life: your health, your contracts, your home.

You shouldn't hand them to an unknown server just to resize them.

That's why nothing is uploaded here. Not today, not when you pay, not ever.

Questions

Are my files uploaded to a server?
No. All processing happens in your browser. Disconnect from the internet to check: the tool keeps working.
Is it free?
Yes. It is free for individuals, with no limits, no watermarks and no ads.
Which files does it accept?
PDF, scanned PDF (with local OCR), Word, Excel, PowerPoint, JPG, PNG and HEIC images, EPUB, HTML and .eml email. Out come Markdown, JSONL, CSV, images or a new PDF.
Can I train a model on my documents?
Yes. The dataset tool turns a folder of PDFs into JSONL in the TRL, OpenAI, Alpaca, ShareGPT, LangChain and LlamaIndex formats, redacted and split by document. All in your browser, or with the CLI on your machine.
What if I'm a company?
Today you can use what anyone can: the web, the CLI and the MCP server, all running on your own machines. The team console, shared templates and data processing agreement are being built, and we are looking for pilot companies to build them with.

For business

Today, the same tools on your own machines. Being built with pilot companies: team console, shared templates and a data processing agreement.

See the business offer

Drop a PDF. See for yourself.

It takes less time than reading this sentence. And your file stays where it was.

Try it now