AI Due Diligence Automation
Build a diligence workflow around your firm's playbook: classify VDR files, extract relevant terms, flag missing support, compare contracts and schedules, and prepare source-backed findings before senior review and IC pressure builds.
What changes for your team
Deal teams receive VDRs with inconsistent folder structures, duplicate files, scanned PDFs, late uploads, and disconnected schedules under compressed timelines. Analysts lose time classifying documents, extracting covenants and change-of-control clauses, checking employee liabilities, comparing customer concentration, and turning findings into a memo format a reviewer can trust.
We build pipelines that ingest CIMs, LPAs, MSAs, vendor contracts, customer schedules, board materials, financial schedules, and management files, then extract agreed data points into structured comparison matrices for analyst review.
Instead of open-ended chatting with documents, the workflow compares files against your firm's risk taxonomy and diligence checklist. It surfaces deviations, missing clauses, unusual obligations, inconsistent figures, and open questions with source references for human judgment.
M&A data is highly confidential and often subject to client, bidder, and counsel restrictions. We design the diligence workflow around the approved data boundary, including dedicated VPC, private cloud, tenant isolation, restricted retention, audit logs, and client-approved model endpoints where required.
How it works
Agree on the work, information, business rules, user roles, desired output, and what the AI is allowed to do.
Bring in only the approved documents, records, business data, control libraries, or playbooks needed for the task.
Give your team findings, matrices, notes, data-backed answers, or work queues with sources and clear reasons for exceptions.
Track edits, accuracy, time saved, exception quality, and adoption before applying the system to more work.
FAQ
Yes, within practical source-quality limits. OCR and table extraction are used first, and low-confidence pages or unreadable tables are flagged for human review.
No. The AI does the exhaustive parsing, extraction, and flagging. It provides exact citations to the source documents so the diligence team can verify the findings and focus on valuation and strategy rather than data entry.
Technology partnership
Have something in mind?