Index a sensitive data room
Point Hexagone AI at an M&A data room. The AI searches, cross-references and flags points of vigilance. The masters stay locked.
Due diligence is a volume problem with a confidentiality constraint bolted to it. Thousands of documents, a fixed deadline, and a deal whose very existence is market-sensitive. The target's name alone can move a price, which rules out the cloud tools that would otherwise make the volume tractable.
How it works
Mirror the room
Point Hexagone AI at the local copy of the data room. It maintains a protected mirror that follows every change as documents are added.
Cross-reference at volume
Because entities stay consistent across the whole room, the model can follow one counterparty through hundreds of contracts, which is the part that makes the analysis worth anything.
Deploy where the deal lives
For transactions that cannot tolerate any outbound connection, the Enterprise plan deploys on-premise or fully air-gapped, with SSO and a command-line interface.
Identify the risky contracts in the data room [c.ACQUISITION_X].
What gets masked here
- Target and acquirer names
- Deal code names and project references
- Valuations, prices and earn-out terms
- Directors, shareholders and key employees
- Customer and supplier concentrations
What you get back
A first pass across the whole room in hours, flagging change-of-control clauses, unusual terms and concentration risk, with nothing about the deal leaving your infrastructure.
How accurate is the detection?Questions on this use case
- Can it be deployed with no internet connection at all?
- Yes. The desktop app works offline after its first install, and the Enterprise plan supports on-premise and fully air-gapped deployment with no outbound network, plus SSO and a CLI for pipeline use. For a deal where the existence of the transaction is itself the secret, that is usually the deciding requirement.
- How does it keep entities consistent across thousands of files?
- The mapping is held for the whole folder, not per document, so one company keeps one placeholder across the entire room. Without that, an AI cannot tell that the counterparty in contract 40 is the counterparty in contract 900, and the cross-referencing that justifies the exercise stops working.
Try it on this exact task.
One week free, no credit card. Nothing is uploaded, so you can run it on a real file without asking anyone's permission.
macOS Apple Silicon and Windows 10/11