Convert documents in your browser

Eight formats — Markdown, HTML, TXT, DOCX, PDF, CSV, JSON, and XLSX — convert in any supported combination, covering the paths people actually travel: Markdown to PDF for publishing, DOCX to Markdown for editing in plain text, CSV to JSON for moving spreadsheet data into applications, PDF to Text for extracting readable content, XLSX to CSV for handing data to tools that speak comma-separated values.

Each conversion page explains what survives the trip and what adapts. Structural formats (headings, lists, tables, links) map faithfully across most pairs; presentation details like fonts and exact layout adapt to what the target format supports natively. The preview renders your source document in the browser, so structural problems surface on your screen rather than in an inbox — and every conversion runs locally, with no upload involved.

Documents carry the details of work and life: contracts, financials, medical letters, unreleased drafts. Uploading them to an unknown converter means trusting someone else's storage, retention, and security practices — a trust decision that is easy to skip when the file is a README and much harder when it is a signed agreement.

Because this converter runs in your browser, none of that applies. Files are read from your device, transformed by JavaScript libraries in memory, and written back to your device. There is no server-side copy to breach, no account to compromise, and no queue — conversion speed depends only on your hardware. It also removes upload limits entirely: a 40 MB document converts as happily as a 40 KB one.

Use the destination as your decision test. If the recipient must read the document exactly as produced — a report, a submission, an archived record — export PDF: fixed layout, embedded fonts, identical everywhere. If they need to edit it, export DOCX for Word users or HTML for web workflows. If a system needs to process the content, export TXT, CSV, or JSON — the formats built for machines rather than eyes.

When in doubt, PDF for reading and DOCX for editing cover almost every human workflow, while CSV and JSON cover the data ones. And because every conversion is reversible where the formats allow it, you can always move back — keeping Markdown as your editing master and exporting derivatives at the point of delivery is a pattern that scales well beyond any single document.

Fidelity is two different promises, and confusing them is how people end up disappointed with a conversion. Structural fidelity — headings stay headings, lists stay lists, tables keep their cells, links keep their targets, code blocks stay monospaced — is what these converters preserve, and it is what matters when a document moves between editable formats like Markdown, HTML, and DOCX. The DOCX preview renders against the document's own settings: page margins, heading styles, and font sizes come from the file itself rather than from a generic template.

Pixel fidelity — every glyph in the exact same position on the page — only exists end-to-end inside PDF, where layout is frozen. When a document crosses between editable formats, presentation details adapt: a typeface unavailable on the rendering device substitutes, column widths reflow to the target, and page breaks recompute for a different page size. That is not a defect; it is what an editable format is for. The workflow that respects both: preview before exporting, verify the structures you care about (the big table, the nested list, the code sample), and reserve PDF for the moment the document is finished — because once it is a PDF, what you verified is what everyone receives.

Data formats are where conversions get subtly lossy, and knowing the traps keeps spreadsheets honest. CSV is pure text: it has no types, no multiple sheets, and no formatting. Convert a spreadsheet to CSV and cell values survive, but formulas become their computed values, sheet structure flattens to whichever sheet was active, and anything text-like that Excel later re-imports is subject to its own reinterpretation — leading zeros in postal codes and account numbers, dates in ambiguous day/month order, and long identifiers that turn into scientific notation.

JSON preserves what CSV cannot — types, nesting, and arrays of records — which is why CSV → JSON suits feeding data into applications, and JSON → CSV suits flattening nested records for spreadsheet analysis (usually one level deep: nested objects either get expanded into dotted columns or stringified). XLSX sits between them: real types, multiple sheets, and formulas, which makes XLSX → CSV a one-sheet extraction — the values of one table, without the workbook around it.

The practical rules: treat the typed format (XLSX or JSON) as the source of truth when types matter, treat CSV as the interchange lingua franca that everything speaks, and never round-trip a sheet with identifiers or formulas through CSV and expect fidelity. Preview the result in the converter — data problems are visible in the first rows — and keep the original file until the export has been checked downstream.