DOCX automation suite
Say goodbye to manual typesetting and tedious copy and paste
Built for Microsoft Word
— Core Capabilities Available Now —
Advanced AI Capabilities Coming Soon
An AI-native automation workflow tailored for Word documents, powered by low-level XML operations.
FAQ
Will formatting change after translating a Word document?
No. SimplifyAI’s proprietary DocumentIR engine works directly on the underlying DOCX XML (Run nodes), preserving bold, italics, font colors, nested tables, headers and footers, footnotes and comments, and even embedded Visio graphic positions and table of contents anchors. After translation, the file can be opened and used directly in Word.
What structured data formats are available for extracted output?
Supports one-click export to highly structured Markdown (with headings and tables) and plain JSON. Ideal as a preprocessing component for enterprise LLM data ingestion and RAG knowledge bases.
Do you support .doc (legacy Word) or WPS formats?
We currently natively support .docx based on the Office Open XML standard (Word 2007+). To process a .doc file, first save it as .docx in Microsoft Word, then upload it. The engine also includes extensive automatic repair handling for invalid XML nodes found in some files saved by WPS.
Can I configure a professional industry glossary before translation?
Yes. The system includes built-in pre-translate analysis, which automatically extracts high-frequency terms and proper nouns from the document. Before translation, you can review them and configure the glossary to ensure consistency throughout the document.
Will layout shift when translating into right-to-left languages such as Arabic?
No. The system includes a built-in RTL auto-mirroring engine. When the target language is Arabic, Hebrew, Persian, or another RTL language, it automatically flips text frames and element alignment after translation, with no manual re-layout needed.
Will translating long documents over 100 pages cause a timeout error?
No. The backend uses a distributed asynchronous processing architecture that automatically splits large documents for parallel processing (fan-out), avoiding LLM token limits and network timeouts, and supporting seamless translation of hundred-megabyte long documents.