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When you upload a document, Zark AI processes its full contents and makes it available for semantic search, extraction, and cross-document analysis. It will never lose context for your uploaded files.

Supported Document Types

Text-based documents are read and indexed so you can ask questions about their content. Zark AI supports the following document formats:
FormatFile ExtensionsExtraction Means
PDF.pdfHandles both text-based and scanned PDFs. Uses optical character recognition (OCR) for image-based documents. Extracts and makes tables queryable. Multi-page documents processed completely with page numbers preserved.
Microsoft Word.docx, .docModern (.docx) and legacy (.doc) formats. Full text extraction with formatting preserved.
PowerPoint.pptx, .pptExtracts text from all slides, including speaker notes, text boxes, and content within shapes. Tables in presentations are captured as structured data.
Plain Text.txtSimple text files with full content extraction and indexing.
Markdown.mdMarkdown-formatted documents with structure and formatting preserved.
HTML.html, .htmWeb pages and HTML documents. Extracts text content and preserves structure.
Rich Text Format.rtfRTF documents with formatting and structure maintained.

What You Can Ask

Once a document is processed, you might ask:
  • “What are the main points in this contract?”
  • “Find any mentions of pricing or payment terms”
  • “Summarize the executive summary”
  • “What action items were mentioned in these meeting notes?”
  • “Does this policy document mention remote work?”
Ask “What does this contract say about liability limitations?” and Zark AI finds the relevant sections even if the word “liability” isn’t explicitly used—it understands the concept you’re asking about.

Cross-Document Analysis

Zark AI can compare and synthesize information across multiple text-based documents, focusing on meaning, language, and intent rather than raw data. This capability also works with data files, allowing you to combine structured data with document content.
Cross-document analysis focuses on understanding meaning, consistency, and intent across multiple text-based documents.
Common use cases include:
  • Identify inconsistencies or conflicts
  • Compare terms, clauses, or language
  • Extract shared themes or differences across documents such as contracts, proposals, reports, or policies.