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Written and reviewed by DeviceterraDeviceterra editorial team · Updated August 2026

KEY TAKEAWAY

A useful document assistant needs clean files, good search, clear sources, correct permissions, and a real test set.

TRY IT YOURSELF

Build the first document collection

A private document assistant has two important jobs. It must find the correct passage and then explain that passage without making up missing facts.

  1. 1

    Create a clean folder

    Make a new folder named approved-documents. Add only current files that users are allowed to search.

  2. 2

    Check every file

    Open each PDF. Make sure text can be selected. Use OCR first when a page is only a scanned image.

  3. 3

    Choose a local document app

    Install a trusted local RAG tool that supports your engine. Confirm in its privacy settings that files and embeddings stay on your device.

  4. 4

    Add five documents

    Do not begin with hundreds. Import five clean documents and let the app create its search index.

  5. 5

    Test known questions

    Ask ten questions with known pages. Confirm the correct passage appears before judging the final AI answer.

How to know it worked
  • Answers show the file name and source passage.
  • The assistant says when the answer is missing.
  • Removing a user's file permission also removes it from that user's search results.
If something goes wrong
  • If the wrong passage appears, fix document extraction or chunking before changing the writing model.
  • If scanned pages are empty, run OCR and import the corrected file again.
UNDERSTAND THE DETAILS

Use the explanations below when you want to know why each step matters.

01

Start with one document group

Choose one useful group, such as staff policies, product manuals, or approved procedures. Decide who will use it and what questions it should answer.

Remove old copies, duplicate files, unreadable scans, and documents with unclear ownership.

02

How the system works

The system reads each document and breaks it into smaller pieces. It turns those pieces into numbers that help a search tool compare meaning.

When a user asks a question, the system finds the best pieces and sends them to the AI model. The model should answer from those pieces and show the source.

03

Build the first version

  • Store approved files locally.
  • Extract the text and check tables and scanned pages.
  • Break text into useful pieces and keep each source name.
  • Create a local search index.
  • Send only the best passages to the model.
  • Show the source and allow the answer “not found.”
04

Test search before testing the answer

Create questions with known source passages. First check whether the search tool finds the correct passage.

If search does not find the evidence, a bigger AI model may not fix the problem. Improve the files, text pieces, or search settings first.

05

Prepare for a team

  • Add user accounts and role-based access.
  • Protect and back up files and search indexes.
  • Keep only the logs you truly need.
  • Place the model and search service behind the app.
  • Create rules for updating and deleting documents.
  • Test again after every important change.
RESEARCH SOURCES

Official facts and real user evidence

Official documentation supports product and model facts. Community discussions show real setups, failures, and questions. A community result is supporting evidence, not a promise that another computer will perform the same way.

MAKE IT PRACTICAL

Find a model your computer can run.

MamiLens checks your hardware and shows a careful starting point.

Run the free compatibility check →

This guide is educational. Model software, licenses, and hardware support can change. Check official sources before an important deployment.