How can AI work with live deal data?

Artificial intelligence (AI) becomes more useful in M&A when it can work with current transaction information rather than static copies of documents. Deals change continuously. New files enter the data room, permissions evolve, diligence questions are answered and transaction teams generate additional information as the process moves forward.

If AI relies on documents exported hours or days earlier, its analysis may not reflect the latest state of the transaction. Working with live deal data creates a different model: AI can interact with information where it is managed while the underlying deal platform continues to govern access.

For dealmakers, the opportunity is to combine current information with AI without sacrificing the permissions, security and auditability surrounding confidential transaction data.

Keep AI connected to current deal information

Traditional AI workflows often require professionals to download documents from a virtual data room (VDR) and upload them into another application. While this can provide useful analysis, it separates the AI workflow from the live transaction environment.

Documents can change after export. New versions may be uploaded, additional diligence materials may become available or access rights may change. Teams can then find themselves analyzing a snapshot rather than the current source of truth.

Secure connectivity offers an alternative. Technologies such as Model Context Protocol (MCP) can allow compatible AI applications to interact with live information maintained within another platform.

An AI-powered deal platform can take this concept further by connecting intelligence with the workflows generating the data. Instead of treating AI as a destination for exported documents, teams can make intelligence part of an evolving transaction environment.

Preserve permissions as deal data changes

Working with live information also creates an important governance requirement. AI access should change when the user's access changes.

If a document is added to a restricted folder, an AI application should only be able to retrieve it for authorized users. If permissions are revoked, the connected application should not continue providing information derived from documents the user can no longer access.

Auditability matters for the same reason. Organizations need visibility into human interactions with confidential information, but AI introduces machine interactions that should also be governed and recorded.

This is where MCP for M&A becomes relevant. MCP can provide the technical connection between an AI application and live deal information, while the transaction platform remains responsible for permissions, governance and control.

The goal is not unrestricted real-time access. It is controlled access to the most current information a specific user is authorized to work with.

Analyze live deal data with DealCentre Connect

SS&C Intralinks DealCentre Connect provides an ecosystem for connecting external AI applications with DealCentre AI™ through secure MCP and API integrations.

The DealCentre Connect Secure Gateway allows external AI tools to work directly with DealCentre, supporting workflows from target sourcing and due diligence to post-merger integration. Intralinks states that organizations can analyze live deal data using specialized or general-purpose AI applications while maintaining data room permissions, governance and auditability.

DealCentre MCP extends this approach to MCP-compatible applications. Rather than downloading and re-uploading confidential documents, authorized AI applications can search, summarize and analyze live deal-room content through the connection. Existing DealCentre permissions continue to determine what information a user can access.

This external connectivity complements Link, Intralinks' proprietary AI engine within DealCentre AI. Link provides native deal intelligence for tasks such as document summarization, critical information extraction and conversational Q&A through Ask Link.

Together, these approaches create a broader model for AI in M&A. Purpose-built intelligence can operate directly within the transaction platform, while connected applications can provide specialized capabilities against authorized live information.

AI working with live deal data should therefore be about more than real-time access. The stronger architecture keeps intelligence synchronized with the transaction while preserving permissions, governance and traceability. That can give dealmakers faster access to current insights without separating AI from the secure environment where the deal is actually happening.