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FAQ

The questions we hear most.

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What is a digest?
A single Markdown file containing the full text of all your sources, with source headers, metadata, and structure preserved. Drop it into any LLM.
Why not just paste my PDFs in?
Pasting drops headings, mangles tables, breaks code blocks, and burns tokens on noise. FileDigest preserves structure and tags sources so the model can reason across them.
Is my data trained on?
No. Files are processed in ephemeral sandboxes. Source files are deleted from storage right after a successful job unless you opt to retain them, and you can delete saved digests at any time.
Do you support OCR?
Yes, on Pro and Business. Docling handles scanned PDFs with layout-aware parsing.
What does FileDigest actually do?
It takes one or more files, such as PDFs, DOCXs, slides, or folders, and produces one ordered Markdown document with section headers, tables, code blocks, and source-file metadata preserved. You paste that document into any LLM. We do not run the LLM for you; we hand you a clean input.
How long does processing take?
A typical 4.5MB cold-start run finishes in about 62 seconds. The same file warm comes back in roughly 17 seconds. Larger jobs scale roughly linearly with token count.
What file formats do you support?
PDF and DOCX are the primary formats. PPTX, XLSX, HTML, Markdown, plain text, common image formats, ZIP batches, and folder picks are supported where the parser can read them.
Do you keep my files?
Source files are deleted from object storage immediately after a successful job unless you explicitly opt to retain them. Processed digests stay in your account until you delete them or delete your account. Full details in our privacy policy.
How is pricing measured?
In LLM tokens - the same units the model sees, roughly 1,000 tokens per 1.5 pages of typical PDF. Free is 3M tokens / month. Pro and Business scale up. See the breakdown on /pricing.
Where do I report a bug or ask for a feature?
Email hello@filedigest.app. We read everything. Bug reports with the job id and a brief description are most useful.