What is a virtual data room (VDR) review?

A Virtual Data Room (VDR) review is the assessment of the repository of documents provided by a borrower or seller during the due diligence process. Analysts review the VDR to identify what information is present, what is missing, and whether the provided data supports the investment thesis.

It is also referred to as "data room due diligence" or "document intake."

What a VDR review includes

A comprehensive VDR review covers:

• File inventory: Cataloging all provided documents, including PDFs, Excel models, legal agreements, and corporate records.
• Gap analysis: Identifying missing materials required for the specific deal type (e.g., flagging a missing balance sheet or customer list).
• Organization: Renaming and sorting files from a chaotic, flat list into a structured hierarchy (e.g., Financials, Legal, HR).
• Preliminary screening: Quickly scanning files to flag extraneous items or potential deal killers like missing tax returns or declining revenue.

How VDR review works with AI

AI accelerates the VDR review by "interviewing" the data room rather than just indexing it.

1. Ingestion: The AI ingests the entire folder structure, parsing nested subfolders and thousands of files instantly.
2. Classification: It automatically categorizes files based on content, distinguishing between, for example, a 2022 tax return and a 2023 board deck.
3. Interrogation: Analysts can use natural language to ask questions like "What materials are missing for me to perform an LBO?" to instantly spot gaps.
4. Risk flagging: The system highlights inconsistencies across documents, such as revenue mismatches between the Audit and the T-12.

Where VDR review is used

• Private equity: For ingesting massive data rooms to evaluate potential buyouts.
• Commercial banking: For reviewing borrower applications containing mixed-format collateral and financial documents.
• M&A transactions: For coordinating due diligence across financial, legal, and operational teams.

Benefits of automated VDR review

• Efficiency: Eliminates the administrative tax of manually organizing, renaming, and filing documents.
• Speed to insight: Allows deal teams to spot missing data immediately — pausing the clock until the borrower provides it — rather than discovering gaps days into the analysis.
• Completeness: Ensures no critical risk document is overlooked in a swath of hundreds of files.

Limitations of VDR reviews

• Unstructured data: VDRs often contain messy data like scanned images or unstructured emails that are difficult to index without advanced AI models.
• Evolving models: As borrowers add new files (v2, v3), analysts must ensure the review process tracks version history and updates.

VDR review FAQs

What is the biggest challenge in manual VDR reviews? 

The lack of consistent naming conventions and folder hierarchies. Borrowers often upload files with generic names (e.g., "Scan01.pdf"), requiring manual review to identify them. AI solves this by understanding the context within the files — not just reading the file names. 

Can AI identify missing documents in a data room? 

Yes. AI agents can compare the uploaded files against a diligence checklist to identify absent items, such as missing tax returns or monthly reporting packets.

Does AI VDR review replace human diligence? 

No. AI organizes and surfaces the information, but the analyst must still evaluate the content of the documents to form an investment opinion.