Technical Due Diligence Checklist: 54 Items to Evaluate Before You Invest or Build

Technical due diligence is the process of evaluating the technology assets, practices, and risks of a company or project. Whether you are acquiring a software company, investing in a startup, evaluating an existing codebase before building on it, or assessing a vendor's technical capabilities, a structured checklist ensures you do not miss critical issues that could cost you months and significant money after the deal closes.

This guide provides a 54-item checklist organized by area, a scoring rubric, red flags to watch for, and a sample summary report format you can use immediately.

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What Is Technical Due Diligence?

Technical due diligence is a systematic assessment of a company's technology stack, development practices, team capabilities, and technical risks. It answers fundamental questions: Is the technology sound? Can it scale? How much technical debt exists? What would it cost to fix the problems?

Unlike financial due diligence, which examines balance sheets, technical due diligence examines codebases, architectures, deployment processes, and the people who build and maintain the software.

Common scenarios where technical due diligence is needed:

• Mergers and acquisitions — assessing the technology assets you are buying
• Venture capital and private equity investment — evaluating whether the technology can support the growth plan
• Pre-build assessment — understanding the state of an existing system before committing to extend or rebuild it
• Vendor evaluation — verifying that a development partner has the technical rigor they claim
• Internal audit — identifying risks and technical debt in your own systems

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Who Should Conduct Technical Due Diligence?

The evaluation requires technical expertise that goes beyond what most business stakeholders can assess on their own. The right evaluator depends on the context:

CTO or VP of Engineering (internal) — suitable when you have in-house technical leadership and the evaluation is for an acquisition or internal audit. They understand your standards and can assess compatibility.

External consultant or fractional CTO — appropriate when you need an independent opinion, lack in-house technical leadership, or want to avoid conflicts of interest in an acquisition scenario.

Development agency — useful when the due diligence is a precursor to a build engagement. The agency assesses the existing technology and then proposes a plan for improvement or extension. This approach works well when you need both the assessment and a team to act on the findings.

Regardless of who conducts it, the evaluation should produce a written report with specific findings, risk ratings, and recommendations — not just a verbal "it looks fine."

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Complete Technical Due Diligence Checklist

Use the checkboxes below to track your evaluation. Each area includes specific items to investigate.

Architecture and Infrastructure

• [ ] System architecture is documented — architecture diagrams exist and are current, showing how components interact
• [ ] Technology stack is appropriate — the chosen languages, frameworks, and databases are suitable for the problem domain and not obsolete
• [ ] No single points of failure — critical services have redundancy; failure of one component does not bring down the entire system
• [ ] Cloud infrastructure is well-configured — resources are properly sized, using infrastructure as code (Terraform, CloudFormation, or equivalent)
• [ ] Database architecture is sound — schema design is normalized appropriately, indexes are optimized, and queries are performant
• [ ] Caching strategy exists — appropriate use of caching layers (Redis, CDN, application-level) to reduce load and improve response times
• [ ] Service boundaries are clear — if using microservices, each service has a well-defined responsibility; if monolithic, the codebase is modular
• [ ] API design follows standards — APIs use consistent patterns (REST, GraphQL), proper versioning, and clear documentation
• [ ] Third-party dependencies are managed — external services and libraries are tracked, and fallback plans exist for critical dependencies
• [ ] Environment parity — development, staging, and production environments are configured consistently to prevent deployment surprises

Code Quality and Technical Debt

• [ ] Codebase is version-controlled — all source code is in a version control system (Git) with a clear branching strategy
• [ ] Code follows consistent standards — coding style is consistent across the codebase, ideally enforced by linters and formatters
• [ ] Technical debt is acknowledged and tracked — known shortcuts and quality issues are documented, ideally in a backlog or tracking system
• [ ] Test coverage is adequate — unit tests exist for critical business logic; integration tests cover key workflows; coverage exceeds 60%
• [ ] Code review process exists — pull requests are reviewed by at least one other developer before merging
• [ ] No critical code smells — the codebase does not have widespread duplication, overly complex functions, or deeply nested logic
• [ ] Dependencies are current — third-party libraries and frameworks are reasonably up to date; no dependencies with known critical vulnerabilities
• [ ] Build process is clean — the application builds without warnings or manual steps; build times are reasonable

Security and Compliance

• [ ] Authentication is implemented correctly — secure password hashing, session management, and support for multi-factor authentication
• [ ] Authorization controls are enforced — role-based access control is implemented and tested; users cannot access data or functions beyond their permissions
• [ ] Data encryption at rest — sensitive data stored in databases and file systems is encrypted using industry-standard algorithms (AES-256)
• [ ] Data encryption in transit — all network communication uses TLS 1.2 or higher; no unencrypted endpoints
• [ ] Input validation is thorough — all user inputs are validated and sanitized to prevent injection attacks (SQL injection, XSS, CSRF)
• [ ] Secrets management is secure — API keys, passwords, and tokens are stored in a secrets manager (AWS Secrets Manager, HashiCorp Vault), not in source code or config files
• [ ] Security testing is performed — regular vulnerability scanning, and penetration testing has been conducted within the past 12 months
• [ ] Compliance requirements are met — if applicable, the system meets regulatory requirements (HIPAA, SOC 2, GDPR, PCI DSS)
• [ ] Incident response plan exists — there is a documented process for handling security incidents, including notification procedures
• [ ] Audit logging is comprehensive — all access to sensitive data and administrative actions are logged and retained per policy

Team and Processes

• [ ] Team structure is documented — roles, responsibilities, and reporting lines are clear
• [ ] Key person risk is mitigated — no single developer holds all knowledge about a critical system; documentation or cross-training exists
• [ ] Development methodology is defined — the team follows a consistent development process (Scrum, Kanban, or a documented hybrid)
• [ ] Sprint velocity is tracked — the team measures and can report on their delivery pace
• [ ] On-call and incident process exists — there is a rotation or plan for handling production issues outside business hours
• [ ] Hiring pipeline is healthy — the team can recruit and onboard new developers within a reasonable timeframe
• [ ] Communication tools and practices — the team uses structured communication (standups, sprint reviews, retrospectives) and appropriate tooling
• [ ] Retention risk is low — key engineers are reasonably satisfied; compensation is competitive; no signs of imminent departure

Scalability and Performance

• [ ] Load testing has been performed — the system has been tested under realistic peak traffic conditions and results are documented
• [ ] Horizontal scaling is possible — the application can run multiple instances behind a load balancer without session or state conflicts
• [ ] Database can scale — read replicas, connection pooling, or sharding strategies are in place or readily implementable
• [ ] Performance monitoring exists — application performance monitoring (APM) tools track response times, error rates, and resource utilization
• [ ] Growth projections are realistic — the team has estimated future load and has a plan for handling 5x and 10x current traffic
• [ ] Cost scaling is understood — infrastructure costs are projected and the cost-per-user or cost-per-transaction is known and acceptable

Documentation and Knowledge

• [ ] Architecture documentation exists — high-level architecture diagrams and descriptions are current and accessible
• [ ] API documentation is complete — all APIs have documentation (Swagger/OpenAPI, Postman collections, or equivalent) that is accurate and up to date
• [ ] Onboarding documentation exists — a new developer can set up the development environment and make their first contribution within 1-2 days
• [ ] Runbooks for operations — documented procedures exist for common operational tasks (deployments, rollbacks, database migrations, incident response)
• [ ] Business logic is documented — complex business rules and domain-specific logic are explained somewhere other than just the code
• [ ] Decision log exists — significant technical decisions and their rationale are recorded (Architecture Decision Records or equivalent)

DevOps and Deployment

• [ ] CI/CD pipeline exists — automated build, test, and deployment pipeline is in place and operational
• [ ] Deployments are automated — production deployments do not require manual steps; they can be triggered by a merge or a single command
• [ ] Rollback process is defined — the team can revert a bad deployment within minutes, not hours
• [ ] Environment management — separate environments for development, staging, and production; environment configurations are managed via code
• [ ] Monitoring and alerting — production systems are monitored; alerts fire for errors, performance degradation, and resource exhaustion
• [ ] Backup and disaster recovery — regular automated backups exist; the team has tested restoring from backup within the past 6 months

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Red Flags to Watch For

These findings should raise immediate concerns during any technical due diligence evaluation:

No version control or poor version control practices. If code is not in Git (or equivalent), or if the team commits directly to the main branch without reviews, the risk of losing work or introducing bugs is extremely high.

Hardcoded credentials in source code. API keys, database passwords, or tokens visible in the codebase indicate a fundamental security gap. If one credential is exposed, assume others are too.

Zero automated tests. A codebase with no tests means every change is a gamble. The cost of adding tests retroactively to an untested codebase is significant and should be factored into any valuation.

Single point of knowledge. If one developer built the entire system and is the only person who understands it, you are one resignation away from a crisis. This is one of the most common and most underestimated risks.

No CI/CD pipeline. Manual deployments introduce human error and slow down delivery. If the team deploys by copying files to a server, modernizing the deployment process should be a top priority.

Outdated dependencies with known vulnerabilities. Libraries that are years out of date and have published CVEs (Common Vulnerabilities and Exposures) represent an active security risk.

No monitoring in production. If the team learns about production issues from customer complaints rather than automated alerts, problems are likely going undetected.

Excessive technical debt with no plan. Some technical debt is normal. Widespread technical debt with no plan or budget to address it signals a team that has been cutting corners for too long.

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Scoring Rubric

Use this rubric to score each area of the checklist on a 1-5 scale. This provides a quantitative summary for stakeholders who need to make investment or acquisition decisions.

| Score | Rating | Description | |-------|--------|-------------| | 5 | Excellent | Best practices are followed consistently. The area is a strength. Minimal risk. | | 4 | Good | Solid practices with minor gaps. Issues are acknowledged and manageable. | | 3 | Adequate | Meets minimum standards but has notable gaps. Improvement needed within 6 months. | | 2 | Below Average | Significant gaps that introduce risk. Requires immediate attention and investment. | | 1 | Critical | Major deficiencies that could impact operations, security, or growth. Potential deal-breaker. |

Area Scoring Summary:

| Area | Score (1-5) | Key Findings | Priority | |------|-------------|-------------|----------| | Architecture and Infrastructure | ___ | | | | Code Quality and Technical Debt | ___ | | | | Security and Compliance | ___ | | | | Team and Processes | ___ | | | | Scalability and Performance | ___ | | | | Documentation and Knowledge | ___ | | | | DevOps and Deployment | ___ | | | | Overall Score | ___ | | |

Interpreting the overall score:

• 4.0-5.0: Strong technology foundation. Proceed with confidence.
• 3.0-3.9: Acceptable with caveats. Budget for improvements identified in the assessment.
• 2.0-2.9: Significant concerns. Factor remediation costs into the deal and secure commitments for improvement.
• Below 2.0: Serious risk. Consider whether the technology is an asset or a liability.

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Sample Summary Report Format

Use this structure for your final due diligence report:

1. Executive Summary (1 page)

• Overall risk rating (Low / Medium / High / Critical)
• Top 3 strengths
• Top 3 risks
• Estimated remediation cost and timeline for critical issues
• Recommendation (proceed / proceed with conditions / do not proceed)

2. Detailed Findings by Area (1-2 pages each)

• Score for the area
• Specific findings with evidence
• Risk assessment for each finding
• Recommended actions with estimated effort

3. Technical Debt Assessment

• Inventory of known technical debt
• Estimated cost to resolve
• Prioritized remediation roadmap

4. Team Assessment

• Team composition and capabilities
• Key person dependencies
• Hiring needs and timeline

5. Appendices

• Architecture diagrams
• Dependency analysis reports
• Security scan results
• Performance test results

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How Long Does Technical Due Diligence Take?

The timeline depends on the complexity of the system being evaluated:

| System Complexity | Typical Duration | Evaluator Effort | |-------------------|-----------------|-----------------| | Simple application (single codebase, small team) | 1-2 weeks | 20-40 hours | | Mid-size platform (multiple services, 5-15 developers) | 2-4 weeks | 40-80 hours | | Enterprise system (complex architecture, large team, regulatory requirements) | 4-8 weeks | 80-160 hours |

These timelines assume cooperation from the target company. If access to code, documentation, or team members is delayed, the process takes longer.

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Next Steps

Need a professional technical audit? ZTABS offers comprehensive technical due diligence for acquisitions, investments, and pre-build assessments. Our team has conducted due diligence on systems ranging from early-stage startup MVPs to enterprise platforms processing millions of transactions. Get in touch to discuss your evaluation needs.

For related resources, see our software vendor evaluation scorecard if you are comparing development partners, or our software development RFP template if you are preparing to solicit proposals for a new build.