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How to prepare private documents for AI without using the cloud
The short answer: keep files in a local-first workflow, inspect what you have, clean and structure the contents, then export only the outputs your AI tools need. This page outlines the process, key decisions, and next steps. [[NEEDS INPUT: body content]]
Summary
What to do first
Preparing private documents for AI is less about chatting with files and more about creating reliable, structured outputs. Start with a clear inventory, review file quality, define metadata rules, and choose export formats that fit your workflow.
1. Inventory your files
List the document types, folders, scans, spreadsheets, images, audio, and notes you want to prepare. Identify duplicates, missing files, and sensitive content boundaries.
2. Clean and convert
Extract text, OCR scans, normalize filenames, and standardize formats so your downstream AI tools are working from usable source material.
3. Add structure
Create metadata, sections, chunks, and source references so records can support search, RAG, review, and automation with traceability.
4. Export for use
Publish structured outputs to the tools you already use, whether that means local folders, Markdown, JSONL, CSV, or a broader AI workflow.
Next step
See what AI-ready looks like
Want a practical starting point? Review Solutions, explore How It Works, or run the File Readiness Pilot to see what can be extracted, structured, and exported from a real file set.