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Overview

Upload Document saves content into the user’s private Bigdata.com corpus and submits it for enrichment and indexing. It is designed for research artifacts — memos, summaries, screens, comparisons, and analyses — so they can be retrieved later with bigdata_search and the private content discovery tools.

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When to Use

Upload Document is ideal for:
  • Saving research artifacts: Persisting memos, summaries, or analyses produced during a session
  • Building a private corpus: Adding tagged notes that remain searchable across future workflows
  • Sharing within the organisation: Optionally making uploaded content available to other members of the organisation
This tool accepts UTF-8 text only (Markdown preferred, HTML, or plain text). For original binary files of any type or size, use https://app.bigdata.com/files. You can also extract text from a PDF or similar file and upload that text as Markdown.

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How It Works

  1. Prepare the content as UTF-8 text (Markdown preferred)
  2. Choose tags using the prefix:value convention (for example topic:semiconductors, project:q3-review). Optionally review existing tags with bigdata_list_tags
  3. Decide sharing: leave private by default, or share with the organisation
  4. Upload with bigdata_upload_document — the response returns immediately while enrichment and indexing continue in the background
  5. Check status later with bigdata_list_documents, or open the file at https://app.bigdata.com/files

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Parameters

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Important Notes

  • Upload is asynchronous. A successful response always returns status="processing"; the document becomes searchable only after enrichment and indexing complete
  • A newly uploaded document may take a short time to appear in bigdata_list_documents while it is registered server-side
  • Binary files (PDF, DOCX, PPTX, and similar) cannot be uploaded through this tool

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Data Returned

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Practical Tips

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Tagging for later retrieval

Use consistent prefix:value tags so content is easy to find with bigdata_list_tags and tag-scoped bigdata_search queries — for example topic:semiconductors or project:earnings-q2-2025.

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After upload

Once enrichment finishes, use bigdata_fetch_document to read the full document, or bigdata_search to retrieve it alongside other private and public content.