A technical due diligence checklist is the guide you will need to find out about potential risks you may not have known before you sign the dotted line. When buying a SaaS business, the underlying technology is a crucial factor in gauging the value of the investment, whereas if you are selling your business, the technology is a key determinant in whether the transaction will be successful or unsuccessful.

Poor technology and integration assessment and risk is one of the top three reasons that M&A deals fall short of value targets, according to Bain & Company. That’s enough to get any buyer or investor’s attention.

Gone are the days of a superficial 5 day code review. Technical due diligence has evolved significantly to cover AI-generated code bases, machine learning models, costs of cloud infrastructure, compliance issues, and team dynamics.

This comprehensive technical due diligence checklist outlines the actual review process that experienced reviewers are doing, the pitfalls that can be fatal and what to prepare if you are the party on the receiving end.

What Technical Due Diligence Actually Covers

Before we dive into the checklist, let’s get clear on what this process is really about. Technical due diligence (TDD) is a structured assessment of a target company’s technology, engineering team, and product delivery capability. It answers one practical question: does the technology behind this business actually support the valuation, the growth plan, and the integration scenario being discussed?

Buyers typically check four things, roughly in this order:

• How the target builds software
• What the target legally owns
• How protected the software is
• How fragile the architecture is

Everything else in a typical M&A due diligence checklist is supporting evidence for these four questions. And here is something most sellers don’t realize: auditors walk in with three reference standards open in front of them. The NIST Secure Software Development Framework tells them what to look for. The OWASP Software Assurance Maturity Model measures how well the target is doing it. ISO 27001 verifies that someone actually owns the result. Sellers who do not know they will be measured against these three get blindsided.

The Complete Technical Due Diligence Checklist

Here is a comprehensive Technical Due Diligence Checklist to help you evaluate a software product’s code, architecture, security, infrastructure, and overall technical health. Use the checklist below to identify potential risks, validate technology assets, and make informed decisions before an acquisition, investment, or technology audit.

Intellectual Property and Legal Ownership

This is where many deals go sideways. You need absolute certainty that the seller has clean, transferable title to the code and assets without legal encumbrances.

What reviewers check:

• Open source compliance. Scanning for copyleft licenses like GPL and AGPL that legally mandate open-sourcing proprietary code
• Contributor rights. Verifying that IP assignment agreements are signed by all past contractors and agencies
• Asset registration. Confirming that domains, cloud accounts (AWS, GCP), and app store accounts are registered to the company entity, not personal emails
• Critical dependencies. Identifying third-party APIs or data sources that could halt operations if they changed terms

Common tools: Snyk or FOSSA for automated scanning of package managers, GitHub Dependency Graph for quick license checks, and Whois lookups for domain verification

Team and Key Person Dependency

A brilliant codebase means nothing if only one person understands how it works. The goal here is assessing whether the technology can operate and evolve without the current founders or lead engineers.

What reviewers check:

• Knowledge silos. Identifying critical system components understood by only one individual
• Admin access control. Checking for shared root passwords or lack of individual identity management for critical infrastructure
• Deployment independence. Verifying the team can deploy code and manage releases without the founder’s physical hardware or input
• Retention criticality. Identifying specific engineers who hold institutional knowledge not documented elsewhere

Common tools: Git shortlog to visualize code contribution percentages (identifies “Bus Factor”), AWS IAM or GCP IAM for auditing user lists

Architecture and Scalability

Can the product grow with the business, or will growth force a major rebuild? This is the core question driving architecture diligence.

What reviewers check:

• Stack standardisation. Evaluating if core programming languages and frameworks are widely used to ensure easy hiring
• Technical debt hotspots. Locating modules with high cyclomatic complexity or legacy code that typically require rewriting
• Database performance. Checking for unoptimized queries, lack of indexing, or architectural bottlenecks that limit concurrent users
• API architecture. Assessing if the system uses modern patterns like REST or GraphQL versus legacy methods that hinder performance

Common tools: SonarQube for automated code quality scanning, Cloudcraft for auto-generating architecture diagrams from live AWS environments, and Locust.io or JMeter for load testing

Infrastructure, Security, and Costs

This area validates the operational balance sheet, security posture, and true cost of delivery.

What reviewers check:

• Cloud waste. Auditing for idle servers, unattached storage, or inefficient resource provisioning
• Unit economics. Calculating the actual hosting and compute cost per user or transaction
• Sensitive data handling. Verifying encryption methods for PII both at rest and in transit
• Disaster recovery. Checking for automated backups and restoration procedures

The security layer goes deeper:

• Policies and procedures
• Security controls and approach (such as Zero-trust)
• Security education across the organization
• Third-party assessments and mitigation approach
• Data privacy and security policies covering PCI, PHI, PII, and GDPR
• Data storage and access permissions
• Monitoring and intrusion detection strategy
• History of breaches and how they were managed
• Compliance requirements and domain-specific compliance needs

AI and Machine Learning (The New Frontier)

This is where the most sophisticated buyers start their diligence. As AI becomes embedded across SaaS products, evaluating the intelligence layer itself is now as important as reviewing the software codebase.

What reviewers check:

• Model architecture and design. What types of models are deployed, how they are trained or fine-tuned, and whether the company builds proprietary models or primarily orchestrates third-party ones
• Training data provenance and ownership. Where training data comes from, whether it is licensed, consented, or proprietary, and whether it creates defensibility or legal exposure
• Third-party model dependencies. Reliance on external LLMs or AI APIs, exposure to pricing changes, performance shifts, or vendor restrictions
• Performance and reliability. Accuracy, hallucination risk, bias mitigation, explainability, and how outputs are monitored and improved over time
• Operational scalability. Compute requirements, inference costs, latency, and whether infrastructure and MLOps practices can scale economically
• Regulatory and legal exposure. Alignment with emerging AI frameworks like the EU AI Act, copyright considerations, and data consent

Strategy and Roadmap

Even the best architecture won’t save a company with a weak strategy. Reviewers evaluate the existence of a clear and cohesive strategy and roadmap process across the organization.

What reviewers check:

• Full SWOT awareness and inclusion in roadmap planning
• Alignment and collaboration with the business roadmap and strategy
• Existence, documentation, and propagation of a reasonable roadmap
• Roadmap feasibility of execution by the team
• Ability to address market needs with clarity on product and service gaps
• Product strategy deep dive including how technology evolves
• Product management planning mechanics and abilities
• Execution discipline and maturity, including backlog health

Organization and Leadership

The goal here is exploring the technology team setup and health. Does the right mix of skills exist to implement the roadmap with cost efficiencies?

What reviewers check:

• The end-to-end organizational setup and reporting structure
• The inter-disciplinary and functions balance
• The ability to attract and retain talent, including attrition trends
• The level of efficiencies in place

How Long Does Technical Due Diligence Take?

The timeline varies based on deal complexity:

• Light engagements take 2 to 4 days
• Standard engagements take 1 to 2 weeks
• Deep engagements for enterprise or regulated targets take 3 to 6 weeks

Add a few days at the start for access provisioning and a few at the end for report writing.

What Does Technical Due Diligence Cost?

Costs have become more standardized:

• Light tech DD runs $5,000 to $15,000
• Standard engagements run $15,000 to $40,000
• Deep engagements for late-stage or regulated companies range from $40,000 to $150,000 plus

A useful rule of thumb is 0.3 to 0.7 percent of deal size, with a $10,000 floor for any software-centric deal.

Red Flags That Kill Deals

Experienced reviewers know exactly what to look for. Here are the deal-breakers that most often reset the purchase price:

• Undocumented technical debt that will require significant investment to mitigate
• Missing IP assignments from contractors or former employees
• Shared admin credentials indicating poor security hygiene
• Single points of failure where only one person understands critical systems
• Skyrocketing cloud costs that don’t scale with revenue
• Open source license violations that could force proprietary code to become open
• No disaster recovery plan or untested backups

How to Prepare If You Are the Seller

If you are on the receiving end of technical due diligence, proactive preparation is your best defense. Here is what works:

• Run a self-imposed tech DD first. Surface and fix issues before they become deal-breakers.
• Organize your data room early. Identify potential areas of concern, gather and organize relevant documentation, and develop impactful presentations for buyer meetings.
• Document everything. Roadmaps, architecture decisions, security policies, and IP assignments should all be well-documented and easily accessible.
• Know your weaknesses. Every codebase has technical debt. The key is knowing where it is, why it exists, and what it will cost to fix.

The Bottom Line

A thorough technical due diligence checklist is not just about risk mitigation. It is about value creation. By treating the process as a strategic opportunity rather than a box-ticking exercise, you can turn scrutiny into strength.

Whether you are the buyer or the seller, the checklist above gives you a complete framework for evaluating technology risk. The companies that prepare thoroughly, document rigorously, and understand their technical position will always have the upper hand at the negotiating table.

The findings that move the price surface in the first three days of diligence. Do not wait until the auditors arrive to discover what they will find. Use this technical due diligence checklist now, and you will be ready for whatever comes your way.