AI is becoming a practical part of due diligence, helping deal teams work through growing volumes of information. While the opportunity is clear, its use also raises an important question: how can M&A professionals benefit from AI-assisted workflows without compromising the security of sensitive deal information or the reliability of the answers they receive?

M&A requires more than a general-purpose AI tool. Dealmakers need responses grounded in authorized project information, traceable to the underlying documents, and subject to human review.

The challenge: finding and verifying deal information

Due diligence involves more than simply locating information. Dealmakers must also understand its context, check the supporting documents, and decide whether it is appropriate to use or share.

This can be a time-intensive process. A team may need to search across numerous files for a single financial figure, identify contracts containing a particular clause, or prepare draft responses to an extensive list of buyer questions.

AI can reduce some of this manual work, but only if teams can verify its output and remain confident that confidential information is protected. In a live transaction, speed has limited value if the answer cannot be traced to a reliable source.

AI built for the M&A process

The Blueflame AI assistant is built into Datasite to help teams work with the contents of their data room, from launch preparation through diligence. Users can ask questions in plain language, search project documents, generate draft answers with source citations, process question lists in bulk, and identify potential gaps before buyer review.

The assistant operates within Datasite’s permission-based environment. It can access only the project content each user is authorized to view, with existing permissions applying to searches, questions, draft answers, and supporting sources. Confidential deal documents remain within Datasite.

Answers are grounded in relevant data room content and, where supporting information is available, include citations linked to the source documents. This allows users to verify the evidence, apply the context of the transaction and refine the response before deciding whether it is ready to share.

The assistant can also process buyer question lists in bulk. Users upload a question list and receive a downloadable Excel file containing draft answers, confidence scores, and available source citations. The deal team remains responsible for reviewing, editing, and approving the responses.

As easy as one, two, three

Using the assistant follows a straightforward prompt, review, and verify process.

1. Ask a question or set a task

Enter a request in plain language within the data room. For example:

• Tell me the FY23 revenue and year-over-year growth.
• Find all employment contracts containing non-compete provisions.
• Run a gap analysis and identify areas to address before go-live.

Teams can also upload a diligence question list for bulk processing.

2. Review the results

The assistant searches the project content available to the user and generates results grounded in the data room. Depending on the task, this may include a draft answer, relevant documents, source citations, or an analysis of potential gaps. It also shows the reasoning and steps used to generate the response, helping users understand how conclusions were reached and verify the output with confidence.

3. Verify the sources

Follow the citations back to the underlying documents, check the details, and apply your own deal knowledge before using or sharing the output. The assistant can also refine and expand its response through back-and-forth dialogue, helping you shape the output to your needs. It supports research and drafting, while the deal team retains responsibility for the final decision.

The assistant supports research and drafting, while the deal team retains responsibility for the final decision.