Which AI platform keeps deal data private?

An AI platform designed to keep deal data private should do more than encrypt information. It should control where confidential documents reside, determine who and what can access them, prevent customer data from training external models and provide an auditable record of how AI interacts with transaction information.

These requirements are particularly important in M&A, where AI may be analyzing financial statements, contracts, intellectual property, employee information and strategic plans. Moving those materials between a virtual data room (VDR) and separate AI applications can introduce additional exposure points.

For dealmakers, the better question is therefore not simply which AI model is most capable. It is which architecture allows teams to use AI while maintaining control over sensitive information.

Keep confidential data within the deal environment

Data privacy starts with minimizing unnecessary movement of transaction information.

Traditional AI workflows may require users to download documents from a secure repository and upload them into another application for analysis. That creates additional copies of sensitive information and can make governance more complicated.

A more controlled architecture allows AI to interact with information where it already resides. Deal teams can then use capabilities such as document summarization, information extraction and conversational search without repeatedly transferring complete documents between systems.

Organizations should also investigate whether customer information is retained or used to train external models. Intralinks explores these considerations in its discussion of why security is becoming a differentiator for AI in M&A.

Make AI access permission-aware and auditable

Keeping documents in a secure environment is only part of the privacy equation. Organizations also need to control what AI can see.

AI should inherit the permissions of the individual using it. If a deal professional cannot access a particular document or folder, the AI application should not be able to retrieve information from that content on the user's behalf.

Organizations should also require traceability and auditability. Administrators need visibility into which AI applications are interacting with transaction information, what users are requesting and whether those interactions remain within established security policies.

This approach is central to DealCentre MCP and secure AI connectivity. Intralinks states that DealCentre MCP validates requests from connected AI tools against existing DealCentre permissions, keeps deal data within Intralinks and logs AI interactions for auditability.

Combine private AI with purpose-built deal intelligence

Privacy should not require deal teams to sacrifice the benefits of AI.

SS&C Intralinks DealCentre AI™ combines AI-powered capabilities with the security and governance controls of an M&A platform. It supports workflows across preparation, marketing, diligence and deal management while keeping transaction information within a controlled environment.

At the center of the platform is Link, Intralinks' proprietary AI engine. Link can summarize documents, extract critical information, identify sensitive content and support conversational analysis. Ask Link allows users to ask natural-language questions about applicable deal documents while respecting existing permissions.

For organizations that want to use compatible external AI applications, DealCentre MCP provides another approach. Rather than downloading confidential documents and uploading them into separate tools, AI applications can connect to DealCentre and work with permitted information in place. Intralinks states that deal data is not permitted to train external or third-party AI models.

For dealmakers evaluating private AI, the architecture matters as much as the intelligence. Keeping information controlled, permission-aware and auditable provides a stronger foundation for using AI without unnecessarily increasing exposure of confidential transaction data.