Technical Due Diligence Checklist for M&A

Buying a software company? The financials might look perfect, but the code could be a ticking time bomb. A single overlooked technical issue can turn a promising acquisition into a costly disaster. At Futureaiit, we have conducted technical due diligence for over 50 M&A transactions, and we have seen deals saved and deals killed by what we found in the code. Here is the comprehensive checklist we use.

Why Technical Due Diligence Matters

Financial due diligence tells you if the numbers are real. Legal due diligence tells you if the contracts are sound. Technical due diligence tells you if the product will still work six months after you acquire it, and whether the engineering team can actually build what the roadmap promises.

We have seen acquisitions where:

The entire codebase depended on one engineer who quit immediately post acquisition
The product was built on end of life frameworks requiring an immediate $2M rewrite
Critical IP was built by contractors without proper assignment agreements
The database schema was so poorly designed that adding new features took 10x longer than expected
Security vulnerabilities exposed customer data, triggering regulatory fines

Each of these issues was discoverable during due diligence. The acquirers who found them either renegotiated the price or walked away. The ones who did not found them paid full price for a technical disaster.

1. Intellectual Property Ownership

You cannot acquire what the seller does not own. Verify that the company actually owns all the code, data, and technology you are buying.

Employment and Contractor Agreements

Request and review:

IP assignment agreements: Every employee and contractor must have signed an agreement assigning their work product to the company
Invention assignment: Ensure the agreements cover inventions created during employment, not just code
Non-compete and non-solicitation: Verify key employees cannot immediately leave and build a competing product

Red flag: Missing agreements for early employees or offshore contractors. This is surprisingly common and can cloud the IP ownership.

Open Source License Compliance

Scan the codebase for open source dependencies and verify license compliance. Use tools like Snyk, FOSSA, or Black Duck to automate this.

Watch out for viral licenses:

GPL and AGPL: These licenses can require you to open source your proprietary code if you distribute or host the software
Creative Commons Non-Commercial: Prohibits commercial use, making the dependency unusable in a commercial product

At Futureaiit, we have seen deals where a single AGPL dependency required either removing the library (expensive) or open sourcing the entire product (unacceptable). Identify these issues early.

Third Party Code and APIs

Verify that all third party integrations are properly licensed. Check:

API terms of service: Can you continue using them post acquisition?
Vendor contracts: Are they transferable or do they terminate on change of control?
Data licensing: If the product uses licensed datasets, can you continue accessing them?

2. Technical Debt and Code Quality

You are not just buying the current product. You are buying the future velocity of the engineering team. Technical debt directly impacts how fast they can ship new features.

Framework and Dependency Versions

Check if the technology stack is modern and maintainable:

End of life frameworks: Python 2.7, AngularJS, Ruby 1.9, PHP 5.x—these are red flags requiring immediate migration
Outdated dependencies: Libraries with known security vulnerabilities or no active maintenance
Custom frameworks: Homegrown frameworks that only the original developers understand

Ask: What is the migration plan? How much will it cost? How long will it take?

Test Coverage and CI/CD

A codebase without tests is fragile. Every change risks breaking existing functionality. Review:

Unit test coverage: Aim for at least 60% coverage on critical paths
Integration tests: Do they test the full stack, not just isolated functions?
CI/CD pipeline: Is there automated testing and deployment, or do engineers deploy manually?

If there are zero tests, assume the product is brittle and expensive to maintain. Factor this into your valuation.

Code Quality Metrics

Use static analysis tools to assess code quality:

Cyclomatic complexity: High complexity indicates code that is hard to understand and maintain
Code duplication: Copy-pasted code creates maintenance nightmares
Code smells: Long functions, deep nesting, god objects—all indicators of poor design

At Futureaiit, we run tools like SonarQube, CodeClimate, or language specific linters to generate objective quality scores. This gives you a data driven assessment, not just subjective opinions.

Documentation

Is the codebase documented? Can a new engineer understand how it works? Check for:

README files explaining how to set up the development environment
Architecture diagrams showing how components interact
API documentation for internal and external interfaces
Runbooks for common operational tasks

Poor documentation means high onboarding costs and dependency on existing engineers.

3. Architecture and Scalability

Can the system handle 10x growth? Or will it collapse under increased load?

System Architecture Review

Request architecture diagrams and review:

Monolith vs microservices: Is the architecture appropriate for the scale?
Database design: Are there obvious bottlenecks or poor schema design?
Caching strategy: How does the system handle high traffic?
Asynchronous processing: Are long running tasks handled properly?

Performance and Load Testing

Ask for load testing results. If they do not exist, that is a red flag. Run your own tests:

What is the response time under normal load?
How does it degrade under 2x, 5x, 10x load?
Are there single points of failure?

Infrastructure and Cloud Costs

Review cloud infrastructure costs and efficiency:

Are they using reserved instances or paying on demand prices?
Is the infrastructure over provisioned or under provisioned?
What will it cost to scale to your projected growth?

At Futureaiit, we have seen companies spending $50k per month on AWS when they should be spending $10k. This inefficiency compounds post acquisition.

4. Security and Compliance

A data breach incident from two years ago can become your liability post acquisition. Thoroughly assess security posture.

Security Audit

Request the most recent penetration test report and review:

What vulnerabilities were found?
Have they been remediated?
When was the last test conducted?

If no pen test exists, commission one as part of due diligence. This is non negotiable for any company handling sensitive data.

Secrets Management

Scan the codebase and git history for hardcoded secrets:

API keys, database passwords, encryption keys
AWS access keys, OAuth tokens, private keys

Use tools like TruffleHog or GitGuardian to automate this. If secrets are found in git history, assume they are compromised and require rotation.

Data Protection

How is customer data protected?

Encryption at rest: Is PII encrypted in the database?
Encryption in transit: Is HTTPS enforced everywhere?
Access controls: Who can access production data?
Audit logs: Are data access events logged?

Compliance Certifications

Verify compliance with relevant regulations:

SOC 2: For B2B SaaS companies
HIPAA: For healthcare applications
PCI DSS: For payment processing
GDPR: For companies with European customers

Request the latest audit reports and verify they are current. Expired certifications mean the company is out of compliance.

5. Team and Knowledge Transfer

The best code is worthless if the team that built it leaves immediately after acquisition.

Bus Factor Analysis

Identify single points of failure in the team:

Is there one engineer who knows how everything works?
Are critical systems documented, or do they exist only in someone's head?
What happens if key engineers leave post acquisition?

Use git commit history to identify who has deep knowledge of each component. If one person has 80% of commits in a critical system, you have a bus factor of one.

Retention Agreements

Negotiate retention bonuses for key technical employees. Losing the lead architect three months post acquisition can derail integration plans.

Knowledge Transfer Plan

Require a structured knowledge transfer plan:

Documentation of critical systems
Pair programming sessions with your engineers
Recorded walkthroughs of the architecture
Access to internal wikis and documentation

How Futureaiit Can Help

At Futureaiit, we provide comprehensive technical due diligence services for M&A transactions. Our team has evaluated companies ranging from $5M acquisitions to $500M deals. We can help you:

Assess code quality and technical debt: Objective analysis using automated tools and manual code review
Verify IP ownership: Review contracts, scan for license violations, identify risks
Evaluate architecture and scalability: Determine if the system can support your growth plans
Audit security and compliance: Identify vulnerabilities and regulatory gaps
Estimate integration costs: Provide realistic timelines and budgets for post acquisition work
Negotiate technical terms: Help structure earnouts, escrows, and warranties based on technical findings

Our reports are designed for both technical and non technical stakeholders. We translate complex technical issues into business impact, helping you make informed decisions.

Conclusion

Technical due diligence is not optional. It is the difference between a successful acquisition and a costly mistake. The issues we have outlined—IP ownership, technical debt, security vulnerabilities, and team dependencies—are all discoverable if you know where to look.

At Futureaiit, we have saved clients millions by identifying deal breakers before the deal closed. We have also helped clients confidently proceed with acquisitions, knowing exactly what they are buying and what it will cost to integrate.

Planning an acquisition? Contact Futureaiit to discuss how we can provide thorough technical due diligence for your M&A transaction.