AI for Due Diligence Automation

Accelerate M&A and vendor due diligence with AI that extracts risks, s

Due diligence spans legal, financial, commercial, IP, privacy, security, and HR checks. AI ingests documents and data rooms, extracts clauses and anomalies, and drafts issue lists.

Human validation, privilege, and auditability are critical.

Clause/obligation extraction, risk classification, anomaly detection,

Review workspace, issue lists with evidence, scorecards, and exports to deal memos.

Feedback from attorneys/analysts, QA sampling, prompt/model versioning, and privilege-aware handling.

live demo · related simulation● LIVE

Implementation Blueprint

Foundation: Define scope and checklists; secure data room ingestion; privilege and access controls; set QA and disclosure policies.

Pilot: Run on a closed deal; measure precision/recall of flags; validate summaries; collect reviewer feedback.

Frequently asked questions

What is the purpose of QA sampling, hallucination tests, and incorporating reviewer feedback?

QA sampling, hallucination tests, and reviewer feedback loops.

How does the system address concerns regarding NDA adherence, access logging, and data retention?

NDA adherence, access logging, retention, and audit trails.

How does the system proactively identify change-of-control clauses and facilitate negotiations?

Change-of-control clauses flagged early; renegotiations planned pre-close.

How does the system highlight data processing gaps with supporting evidence, leading to remediation?

Data processing gaps surfaced with evidence, driving remediation plan.

▶ Try it live

Everything above runs in your browser — open Hash Function Avalanche Visualizer and change the parameters while it is running. Nothing is installed, nothing is uploaded, the whole model lives in one tab.

▶ Open Hash Function Avalanche Visualizer simulation