● AI Agent  ·  M&A / Private Equity

M&A Due Diligence AI Agent — Reads Every Data Room Document, Surfaces Every Material Risk

Your attorneys are billing $500/hour to read documents. Most of that is data extraction — not judgment. This AI agent reads every document in the data room, flags every material risk, and delivers the diligence memo — so your deal team spends their time on decisions, not reading.

👈  Live demo below. Walk through the same steps the AI runs on a real deal — from data room intake to completed diligence memo. Hit Run Demo to auto-play all five steps.
Weeks
manual doc review → days
$500/hr
attorney doc review replaced
Zero
material risks missed at close
PROJECT ATLAS — DUE DILIGENCE SUMMARY CONFIDENTIAL DILIGENCE PROGRESS Financials COMPLETE Legal / Contracts 75% Intellectual Property 50% HR / Employment 30% MATERIAL RISK FLAGS — 6 ITEMS HIGH Revenue concentration: top 3 customers = 68% of ARR MED Change of control clause in 4 of 11 customer contracts HIGH IP assignment incomplete: 2 of 6 founders not on record MED Earn-out clause undisclosed until page 42 of LOI AI analyzing data room ✓ 312 pages processed 312 pages read 6 risk flags 18 docs reviewed ✓ Diligence memo generated — ready for deal team review
The Problem

A typical M&A data room has 200–500 documents.
Someone has to read every one.

Financial statements, customer contracts, employment agreements, IP assignments, disclosure schedules, board minutes. The information is all there — buried in dense documents across dozens of folders. The issue isn’t access. It’s time, cost, and the risk of missing something material.

⚠  What the data room looks like
📄  ProjectAtlas_CIM_v4_FINAL.pdfPDF · 94 pages
⚠ Revenue concentration risk on page 61. Not in the exec summary.
📊  Financials_FY21_FY22_FY23_Audited.xlsxXLSX · 14 tabs
⚠ Deferred revenue treatment changes in FY23. Requires reconciliation.
📄  CustomerContracts_Folder_11_docs.pdfPDF · 11 contracts
⚠ Change-of-control clauses in 4 contracts. Only findable by reading every page.
→
✓  What the AI delivers
AI Extraction — Customer Contracts (11 docs)
Total contracts reviewed11 of 11Complete
Change-of-control clauses4 contractsFlag ⚠
Auto-renewal provisions7 contractsReview
Termination-for-convenience3 contractsFlag ⚠
Weighted avg. contract value$284k/yrExtracted
Top customer % of ARR38%Concentration
Deal risk:4 customer contracts may require consent at close
📄  The AI does this across every document category simultaneously — financials, contracts, IP, HR, tax — and assembles one structured diligence memo.
●  Interactive Demo — Project Atlas Acquisition

Walk through each step the AI runs on a real deal. $47M target company, 18 data room documents, 312 pages. Click any document to watch the AI read it, or hit Run Demo to auto-play.

Project Atlas  ·  Due Diligence Workspace  ·  $47M Target  ·  18 Documents
Data room intake — 18 documents across 5 categories
The AI agent processes each document the moment it’s uploaded to the data room. PDFs, spreadsheets, Word documents, and scanned filings are all read automatically. Click any document to watch the AI work through it, or hit Run Demo to process all eighteen.
18
Documents
312
Pages
6
Risk Flags
4
Need Action
Financial & Operating
01
Confidential Information Memorandum (CIM)
PDF · Management prepared · FY2021–FY2023
PDF
94 pp
Pending
02
Audited Financial Statements FY21–FY23
XLSX · Big 4 audited · 14 tabs
XLSX
62 pp
Pending
03
Customer Contracts (11 agreements)
PDF · Enterprise & mid-market · Compiled
PDF
88 pp
Pending
Legal & Corporate
04
Certificate of Incorporation & Bylaws
PDF · Delaware C-Corp · As amended
PDF
18 pp
Pending
05
Cap Table & Stock Option Agreements
XLSX · Current as of Q4 2024
XLSX
24 pp
Pending
Intellectual Property
06
IP Assignment Agreements (Founders)
DOCX · 6 founder agreements · Executed
DOCX
26 pp
Pending
💡  Connects directly to Intralinks, Datasite, SharePoint, or any shared drive your target uses. Documents are picked up automatically as counsel uploads them — no one on your team has to move files or trigger anything.
CONNECTS TO Intralinks 📄 Intralinks Datasite 📄 Datasite 📄 SharePoint Outlook Outlook DocuSign 🖊 DocuSign 📊 Excel
BUILT WITH Claude Claude AI n8n n8n Make.com Make.com
The AI reads the raw document and extracts every material term
Left: the actual document from the data room. Right: the AI extracting facts, flagging risk items, and noting anything that requires deal team attention. Select a document below.
Raw document from data room
CIM v4 FinalPDF · 94pp
AI extraction — material findings
Extracting & classifying findings
Ready
Select a document above to begin extraction.
All diligence findings structured by category
Every material finding extracted across all data room documents, organized by diligence category. Toggle between the summary view and the detailed findings with risk ratings.
6 documents reviewed · 312 pages · 6 risk flags identified
Material risk flags — what the deal team needs to address before close
The AI identified 6 material risk items across 4 document categories. Two require immediate deal team action before the LOI is finalized. These are the findings that would have cost weeks to surface manually — or would have been missed entirely.
Revenue concentration — top 3 customers are 68% of ARR
High Risk
The CIM presents a “diversified” customer base, but the financial detail shows that the top 3 enterprise customers account for 68% of annual recurring revenue. One of these customers has a contract renewal in 18 months with no signed extension.
Requires deal structure adjustment — escrow or earn-out tied to customer retention.
IP assignment incomplete — 2 of 6 founders not on record
High Risk
Four of the six founder IP assignment agreements are fully executed. Two are either missing or reference a prior version of the agreement that predates the company’s current IP ownership structure. This creates a potential ownership gap in core technology assets.
Must be remediated before close. Counsel to obtain executed assignments from both founders.
Change-of-control clauses in 4 customer contracts
Medium Risk
Four of the eleven customer contracts include change-of-control provisions that require customer consent upon acquisition. Three of these are enterprise contracts representing approximately $2.1M of ARR combined. The fourth is a government contract subject to additional regulatory review.
Customer consent outreach should begin in parallel with deal process. Do not wait until signing.
Deferred revenue accounting changed in FY2023
Medium Risk
The audited financials show a change in deferred revenue recognition methodology between FY2022 and FY2023 that inflated reported ARR by approximately 11%. The footnote disclosure is on page 38 of the financial statements and is not referenced anywhere in the CIM or management presentations.
Adjust valuation model. Work with financial advisor to restate ARR on a consistent basis.
Key employee retention — CTO has no vesting cliff post-close
Note
The CTO’s equity is fully vested at close. There is no retention agreement or post-close vesting schedule in place. Given the CTO’s role as lead architect of the core product, departure within 12 months post-acquisition represents meaningful continuity risk.
Negotiate retention package with multi-year vesting as a condition of close.
Corporate structure — clean Delaware C-Corp, no issues
Clear
Certificate of incorporation, bylaws, and board consents are all in order. No outstanding litigation, regulatory proceedings, or undisclosed liabilities surfaced in the corporate documents. Cap table is clean with no unusual provisions.
No action required. Corporate documents ready for closing checklist.
The AI drafts and sends the diligence memo to your deal team
Once the data room is processed, the AI generates a structured diligence memo and sends it to the managing partner, deal counsel, and financial advisor. Every material finding, risk flag, and recommended action — in one document.
Gmail  ·  AI-generated diligence memo
diligence-agent@atlasadvisors.com
TO
r.chen@atlasadvisors.com, s.bishop@atlasadvisors.com, m.okonkwo@dealcounsel.com
SUBJECT
PROJECT ATLAS — Diligence Memo · 6 Docs Reviewed · 2 High-Risk Items
📄  Full Findings Matrix.sheets  ·  Risk Register.pdf  ·  Action Checklist.docx
How it works

Three steps. Fully automated.

From data room upload to structured diligence memo — without your team spending weeks on document review.

📤
Step 1
Documents are uploaded to the data room
Connects directly to Intralinks, Datasite, SharePoint, or your shared drive. The moment the target’s counsel uploads a document, it’s picked up and queued. PDFs, Excel models, Word docs, and scanned filings all work.
Orchestrated by n8n or Make.com — the automation layer that connects your data room to the AI pipeline.
📄
📄
📂
n8n Make.com
→
🤖
Step 2
The AI reads every document and extracts material terms
Claude AI reads each document with the same focus a diligence attorney brings to document review. It extracts financial metrics, contract terms, IP ownership, risk factors, and anything that could affect deal structure or valuation — and flags every item that warrants deal team attention.
Replaces $500/hour attorney review for the document extraction phase. Your attorneys focus on judgment, not reading.
Claude AI
→
📋
Step 3
Deal team gets the structured diligence memo
The memo lands in your deal team’s Outlook inbox, structured by diligence category with risk ratings and action items. Findings push into your DealCloud deal record or an Excel tracker — wherever your team manages the deal file.
Can also push to Google Sheets, Airtable, or any deal management system with an API. We build to your workflow, not ours.
Outlook
▪
📊
Sheets Airtable
What this replaces

Law firms bill $500/hour for document review.
That adds up fast on a 300-page data room.

Here’s what deal teams are paying today for diligence document review — and what they pay when we build this instead.

Big Law document review Current
$500+/hr
per attorney · 300-page room = $40k–$120k
Expert legal judgment
Can negotiate and advise
$500/hr for document reading
2–6 weeks for full review
Things still get missed
Kira / Luminance AI Current
$30k–$100k
per year · enterprise contract
Purpose-built for legal review
Good clause extraction
Requires attorney training to use
Not connected to your workflow
You rent it forever
Junior associate review Current
Weeks
per deal · 2–4 associates on a typical deal
Learns the deal context
Can ask follow-up questions
2–4 weeks per data room
Fatigue leads to missed items
Inconsistent output quality
Omni AI Agent What we build
You own it
one-time build · no per-deal fees
Reads every document automatically
Consistent output on every deal
Flags material risks before close
Delivers structured memo to team
You own it — not a subscription
Demo Notice: Conceptual demonstration of an AI-powered M&A due diligence workflow. All company names, financial figures, deal terms, and document contents are illustrative and do not represent real transactions or entities. This is not legal advice. Omni Online Strategies builds custom AI automation systems — every engagement is scoped to your specific deal process, document types, and workflow requirements.
Josh Leavitt — Founder, Omni Online Strategies
From the founder
“Every PE deal I’ve talked through has the same story somewhere in it — something material that was in the data room but wasn’t surfaced until after close. Not because the attorneys weren’t good. Because 300 pages is a lot to read under time pressure when you’re billing by the hour.”
The information is always there. The IP assignment gap, the revenue concentration, the change-of-control clause — it’s in the documents. The question is whether someone finds it before you wire the money. This agent makes sure they do, on every deal, without adding weeks to the timeline.
Josh Leavitt
Founder & CEO · Omni Online Strategies

Let’s talk about your deal process →