Due-diligence document review
M&A and regulatory due diligence involves reviewing thousands of documents under a tight timeline. Throughput is capped by the number of lawyers the firm can throw at it.
AI extracts, classifies and summarises every document, builds the DD log as it goes, and flags the handful of documents that contain real risk.
- 01
Documents are ingested from the data room, preserving privileged access controls.
- 02
Each document is classified by type (material contract, HR, IP, financial) and summarised against your DD taxonomy.
- 03
Risk signals (change of control, unusual liability, indemnity language) are flagged with the exact passage.
- 04
The DD log is built automatically as the review proceeds, with lawyer review concentrated on flagged items.
- 05
A final report is drafted from the log and reviewed by the lead partner.
with 2x to 3x DD throughput without adding lawyers.
Ranges drawn from production deployments and public enterprise benchmarks. For a specific rupee or dollar figure tailored to your volume, use the calculator below.
Prerequisites for a clean deployment.
- Secure access to a virtual data room
- A DD taxonomy appropriate to the deal class
- A reviewer playbook (what to flag, what to ignore)
- Lead partner oversight and sign-off authority
Put your own numbers on it.
“At 1,000 documents a month and a loaded monthly cost of ₹1,50,000 per person, due-diligence document review would typically save ₹7.5 L to ₹11 L a year.”
Range uses this use case’s typical automation rate (50 to 75 percent) against the baseline time per task for documents work, with your cost per person converted at 160 working hours a month.