Use cases
Ways teams use FileDigest to turn messy documents into clean, AI-ready context, plus how it compares to pasting files into ChatGPT, Claude, or the Docling CLI.
FileDigest does one job: it compiles a folder of documents into one clean, source-labeled context pack for ChatGPT, Claude, RAG, and agents. Below are the most common ways people use it, and a few honest comparisons. Every page links back to the same product.
By workflow
- Consulting document packets: bundle a client's mixed files into one reviewable context pack.
- Research paper digestion: turn papers into clean Markdown you can actually feed a model.
- RAG document ingestion prep: get heading-contextualized chunks ready to embed.
- LLM context pack generator: produce one context file from many documents.
- ZIP to LLM context pack: drop a ZIP, get a single context pack back.
By conversion
- PDF to Markdown for AI
- Prepare a PDF for ChatGPT
- Prepare a PDF for Claude
- DOCX to Markdown for ChatGPT
- OCR a scanned PDF to Markdown
By tooling and format
- Hosted Docling UI
- Run a Docling workflow on Modal GPUs
- manifest.json for processed documents
- Private, secure document processing
How it compares
Want the short version instead? Read how FileDigest works or download a real example packet.