VirtualVaults

Virtual Vaults is a cloud-based virtual data room and deal management platform designed to support secure document sharing, collaboration, and workflow management across complex transactions such as mergers and acquisitions, private equity deals, real estate transactions, and legal processes. Founded in 2014 and headquartered in the Netherlands, the platform is positioned as an end-to-end environment for managing the full deal lifecycle, from preparation through due diligence to post-deal archiving.

The platform combines traditional virtual data room functionality with broader deal preparation and workflow tools. It enables teams to organize large volumes of documents, manage access rights, and collaborate securely with internal and external stakeholders. By integrating preparation, execution, and archiving within a single system, Virtual Vaults aims to reduce fragmentation across tools and improve control and transparency throughout transaction processes.

A key component of the platform is its “Workspaces” functionality, which allows users to prepare deals in advance by organizing documents, assigning tasks, and managing collaboration before moving content into a secure data room for due diligence. The platform also includes features for secure file sharing, Q&A management, and audit tracking, enabling structured interaction between buyers, sellers, and advisors during transactions.

Virtual Vaults places strong emphasis on security and compliance, incorporating features such as encryption, multi-factor authentication, audit logs, and ISO 27001-certified information security management practices. These capabilities are designed to support the handling of sensitive financial, legal, and corporate data in high-stakes transactions.

The platform is typically used by investors, advisors, law firms, and corporate teams involved in dealmaking, particularly in mid-market M&A and related transactions. It is delivered as a SaaS solution with predictable pricing and unlimited storage, supporting scalability for data-intensive use cases.