M&A Due Diligence — AI-Augmented Assessment#

Run a structured due diligence analysis on any acquisition target. Covers financial, operational, technology, legal, cultural, and AI/automation readiness dimensions.

When to Use#

• Evaluating an acquisition target
• Preparing sell-side due diligence materials
• Assessing a merger partner
• Running post-LOI deep dive
• Investor or board due diligence request

How to Use#

Tell your agent: "Run M&A due diligence on [Company Name]" or "Prepare due diligence for acquiring [target]."

The agent will walk through each dimension below and produce a scored assessment with red flags, deal-breakers, and a go/no-go recommendation.

Due Diligence Framework#

1. Financial Health (Weight: 30%)#

Revenue Quality Score (0-100)

FactorWeightCheckRevenue concentration25%Top client <15% of revenue = green, >30% = redRecurring vs one-time25%>70% recurring = green, <40% = redRevenue growth trend20%3-year CAGR >15% = green, declining = redGross margin15%>60% SaaS / >40% services = greenCash conversion15%Operating cash flow / EBITDA >80% = green

Financial Red Flags

• Revenue recognized before delivery
• Related-party transactions >5% of revenue
• Working capital deteriorating quarter-over-quarter
• Customer acquisition cost (CAC) payback >18 months
• Deferred revenue declining while bookings "grow"
• Off-balance-sheet liabilities or operating leases hiding debt

Valuation Sanity Check

MetricHealthy RangeDanger ZoneEV/Revenue3-8x (SaaS), 1-3x (services)>15x without hypergrowthEV/EBITDA10-20x>30xPrice/FCF15-25x>40x or negative FCFNet debt/EBITDA<2x>4x

2. Technology & Product (Weight: 20%)#

Tech Stack Assessment

• Architecture: Monolith vs microservices vs serverless
• Technical debt score: deployment frequency, change failure rate, MTTR
• Security posture: SOC 2, ISO 27001, penetration test recency
• Scalability: Can 10x current load without rewrite?
• AI/Agent readiness: API-first? Automation potential?
• IP ownership: Clean IP assignments from all contributors?

Product-Market Fit Signals

• Net Revenue Retention >110% = strong PMF
• Logo churn <5% annually = healthy
• NPS >40 = good, >60 = excellent
• Organic growth % of total = true demand signal

3. Legal & Compliance (Weight: 15%)#

Legal Checklist

• Pending or threatened litigation
• IP infringement claims or risk
• Data privacy compliance (GDPR, CCPA, HIPAA)
• Employment law compliance (contractor misclassification)
• Environmental liabilities
• Tax compliance and audit history
• Change-of-control clauses in key contracts
• Non-compete/non-solicit enforceability

Regulatory Risk Score

• Industry-specific regulations mapped
• Compliance cost as % of revenue
• Pending regulatory changes that could impact operations

4. Operational Excellence (Weight: 15%)#

Operations Scorecard

AreaGreenYellowRedEmployee turnover<15%15-25%>25%Key person dependencyDistributedSome concentrationSingle point of failureProcess documentationComprehensivePartialTribal knowledgeVendor concentrationDiversified2-3 criticalSingle vendor lock-inCustomer support quality<2hr response, >90% CSAT4-8hr, >80% CSAT>24hr, <70% CSAT

5. Cultural & People (Weight: 10%)#

Integration Risk Assessment

• Leadership alignment on vision and values
• Compensation structure compatibility
• Remote/hybrid/office culture match
• Decision-making style (flat vs hierarchical)
• Glassdoor/Blind sentiment analysis
• Key employee retention risk (flight risk score)

Retention Package Benchmarks

Role LevelRetention PeriodTypical PackageC-Suite12-24 months1-2x base + equity accelerationVP/Director12-18 months0.5-1x base + equityKey IC6-12 monthsSpot bonus + equity refresh

6. AI & Automation Readiness (Weight: 10%)#

Agent-Era Value Score

• Data quality and accessibility (structured, labeled, API-accessible?)
• Process automation potential (which workflows can agents run?)
• AI talent on team (ML engineers, data scientists, prompt engineers)
• Existing AI/ML models or IP
• Competitive moat from proprietary data or models

Post-Acquisition AI Uplift Estimate

DepartmentAutomation PotentialAnnual SavingsCustomer Support40-60% ticket deflection$120K-$400KSales Operations30-50% pipeline automation$80K-$200KFinance/Accounting50-70% reconciliation$60K-$150KHR/Recruiting40-60% screening$50K-$120KLegal/Compliance30-40% contract review$40K-$100K

Scoring & Output#

Overall Deal Score (0-100)#

• 80-100: Strong buy — proceed to LOI/definitive agreement
• 60-79: Conditional — address specific risks before proceeding
• 40-59: Caution — significant risk areas need resolution
• 0-39: Walk away — deal-breakers present

Deal-Breaker Triggers (auto-fail regardless of score)#

• Undisclosed material litigation
• Revenue fraud or restatement risk
• Key customer representing >40% revenue with no contract
• Unresolvable IP ownership dispute
• Regulatory action that could shut down operations
• Key founder/employee departure with no retention agreement

Output Template#

text

# M&A Due Diligence Report: [Target Company]
Date: [YYYY-MM-DD]
Prepared for: [Acquirer]

## Executive Summary
- Overall Score: [X/100]
- Recommendation: [BUY / CONDITIONAL / WALK]
- Key Strengths: [3 bullets]
- Critical Risks: [3 bullets]
- Estimated Integration Cost: $[X]
- Post-Acquisition AI Uplift: $[X]/year

## Detailed Scores
| Dimension | Score | Weight | Weighted |
|-----------|-------|--------|----------|
| Financial Health | /100 | 30% | |
| Technology & Product | /100 | 20% | |
| Legal & Compliance | /100 | 15% | |
| Operational Excellence | /100 | 15% | |
| Cultural & People | /100 | 10% | |
| AI & Automation Readiness | /100 | 10% | |
| **Overall** | | | **/100** |

## Red Flags
[Numbered list with severity and mitigation]

## Integration Roadmap
- Day 1-30: [Quick wins]
- Day 31-90: [System integration]
- Day 91-180: [Full operational merge]
- Day 181-365: [Optimization and AI deployment]

## Recommended Next Steps
[3-5 specific actions]

2026 Benchmarks#

M&A Market Context

• Average SaaS acquisition multiple: 6-10x ARR (down from 15-20x in 2021)
• Due diligence period: 60-90 days (accelerating with AI tools)
• Integration failure rate: 70-90% of M&As fail to deliver expected value
• #1 reason for failure: Cultural mismatch and poor integration planning
• AI-ready targets command 15-25% premium over comparable non-AI companies

What's Changed in 2026

• AI/agent readiness is now a core valuation driver
• Data assets valued separately (proprietary training data = moat)
• Per-seat SaaS revenue declining — usage-based models preferred
• Remote-first companies easier to integrate (no office consolidation)
• Regulatory complexity increasing (EU AI Act, state privacy laws)

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