How to Review a Document with an AI Team

AI document review means handing a draft to AI models and getting back specific, section by section feedback you can act on. With aiDex you can go a step further than a single model: a whole team of models reads the same file at once, so different reviewers catch different problems. Here is how to do it.

Why use several AI models to review one document?

One model gives you one perspective. A team gives you several, and they rarely flag the same things. One reviewer might catch a structural gap, another a factual claim that needs a source, another an awkward phrasing or a risk in the wording. Because each model has different strengths, a panel surfaces more real issues than any single pass would, and you stay in control of which fixes land.

This is the same multi-model idea behind a debate between AI models, applied to a document instead of a question. If you are new to running models as a group, the Multi-Model AI Workflows guide is the place to start.

How do I get an AI team to review my document?

There are two ways to begin, and both end in the same place: a team reading your file.

1. Upload into a chat. Start a chat and attach your document. aiDex accepts DOCX, PDF, Markdown, and plain text. The file is read into the conversation so the team can work from the full text, not a summary you paste in.
2. Use the Document Revisors team. aiDex ships a preset Document Revisors team built for exactly this job. Pick it, attach your file, and the panel is already configured to read and critique a document.

Either route puts a team of models on your draft. You choose the models behind the team from OpenAI, Anthropic (Claude), Google (Gemini), DeepSeek, or a local model through Ollama. Use your own provider keys or the ones we manage, and pick the models you want. If you want help matching a model to the kind of writing you are reviewing, see Which AI Model for Which Task?.

What does the team actually flag?

Once the team reads the document, it returns issues organized by section and by type. Types include things like clarity, structure, factual, style, and risk, so you can tell at a glance whether a note is about how something reads or whether a claim needs checking.

Each issue shows up as a suggestion card in a side panel next to the document. That layout keeps every flagged item tied to the part of the text it refers to, instead of burying feedback in a long chat reply.

How do I accept or reject the suggestions?

Work through the cards in the side panel one at a time. Each suggestion has an accept or reject control, so you decide which changes you actually want. Reject the ones that miss the point or that you disagree with, and accept the ones that improve the draft. Nothing is changed for you automatically; the accepted set is what carries forward.

This is the important part of AI document review: the team proposes, you dispose. You keep editorial control over every edit.

How do I get the revised file back?

This depends on the file type, and the difference matters.

• DOCX: after you accept suggestions, you can generate a revised .docx. aiDex runs an Editor plus Reviewer pass to produce the new file, which you can download and open in your usual word processor.
• PDF: PDFs are suggestions only. You get the full review and the flagged issues, but there is no edited file to download. If you need an edited output, convert the source to DOCX first and upload that.

So if your goal is a clean, revised document you can hand off, work from a DOCX. If you only need the critique, a PDF is fine.

Will the revision change my document's language?

No. A generated revision stays in the document's original language. If you uploaded a Spanish contract, the revised .docx comes back in Spanish, even if your aiDex interface is set to English. The revision follows the source text, not your interface language, so a translated draft is never an accident of the review.

Tips for reviewing large documents

Long files reward a little structure:

• Lead with the issue types that matter most. If you are checking a legal draft, prioritize the factual and risk cards before polishing style.
• Work section by section. Because issues are grouped by section, you can clear one part of the document before moving to the next instead of jumping around.
• Split very long documents. For a book-length file, reviewing in logical chunks keeps each pass focused and the suggestion list manageable.
• Re-review after big changes. Once you have accepted a round of structural edits, run the team again so it reacts to the updated draft rather than the original.
• Match the team to the document. A technical spec and a marketing page benefit from different model strengths, so adjust the team behind the review when the material changes.

That is the whole loop: upload or pick the Document Revisors team, let the panel flag issues by section and type, accept or reject each card, and for a DOCX export a revised file in its original language. A team of models reading together simply catches more than one model reading alone.