Perfect your M&A practice

An end-to-end M&A platform should cover pipeline, diligence and integration in one system with a shared data model. Look for customizable deal phases and fields, a request list that doubles as a template, a built-in data room with folder-level permissions, Findings that carry into integration planning, task dependencies with a timeline view and reporting that reads from all of it. DealRoom adds native AI for document review and an MCP server so your own agents can work with the same deal data.

DealRoom is built as the Operating System for Buyer-Led M&A™, which shapes three things. First, the workflow is designed for buy-side teams running repeat acquisitions, so request lists, permission groups and integration plans are saved as templates and reused deal after deal. Second, AI is native to diligence and pipeline, cites its source passage and says when documents do not contain an answer. Third, the same deal data is open to your own agents over MCP and to BI dashboards built on Looker.

Yes, an M&A platform should take your current Excel tracker rather than make you rebuild it. DealRoom imports existing diligence request lists from Excel. During onboarding a customer success manager will load your tracker and folder structure into a room for you. Once imported, the list becomes a request template with status, assignees, priority and due dates that you reuse on the next deal. Bulk user invites and drag-and-drop upload get documents and people in the same day.

An M&A platform keeps deal knowledge by saving the artifacts of each deal as reusable templates and records. In DealRoom, request lists, data room folder structures, permission groups and integration plans are stored as templates. Findings record risks, assumptions and mitigation plans with owners. Timestamps on every stage move build a history that BI reports on. The result is an institutional record that stays when people move on, so each deal starts from the last one rather than from scratch.

DealRoom AI runs predominantly on OpenAI models today and is LLM agnostic by design, so DealRoom can select across models for speed, cost and accuracy. Content sent for inference travels over an encrypted connection and is used for inference only; model providers do not train on it. DealRoom does not use customer data or conversations to train models. Customers retain ownership of their data. AI features can be disabled at the organization level. Terms: https://dealroom.net/legal/ai-feature-terms

Yes, DealRoom integrates with Salesforce. CRM hand-offs such as HubSpot for early outreach can be configured. Around the CRM, DealRoom offers an Outlook add-in and a Gmail add-in that link emails to deals, Apollo.io and PitchBook enrichment for deal cards, Slack notifications, SSO through Okta or Azure AD plus an open API. For AI tools, an MCP server lets agents such as Claude and Microsoft Copilot read deal data within each user's permissions.

An end-to-end M&A platform is built for repeat acquirers: corporate development teams running three or more deals a year, often at the same time, with senior dealmakers spending most of their time on coordination. DealRoom's customers include teams asked to do more deals with the same headcount, teams that have lost institutional knowledge as people left and teams exploring AI but cautious about tools with no M&A context. Sellers, external counsel and advisors join as unlimited users without training.