Technical Due Diligence Checklist for Pre-Series A Startups

Investors evaluating pre-Series A startups need a systematic approach to assess technical risk. Unlike later-stage companies with established engineering practices, early startups often prioritize speed over structure. This creates unique challenges when conducting technical due diligence.

This comprehensive technical due diligence checklist helps investors and advisors evaluate code quality, architecture decisions, security practices, and team processes. The goal isn't finding perfect code—it's identifying deal-breaking technical debt and assessing the team's ability to scale.

Prerequisites for Technical Due Diligence

Before diving into code review, gather these materials from the startup:

• Access to primary code repositories
• Architecture documentation (even basic diagrams)
• Current deployment and infrastructure setup
• Team structure and development processes
• Recent security audit results (if available)

Code Quality Assessment

Repository Structure and Organization

Start by examining how the codebase is organized. Well-structured repositories indicate disciplined development practices, even in early-stage companies.

Check for consistent naming conventions across files and folders. Look for separation of concerns—frontend code shouldn't be mixed with backend logic without clear boundaries. A startup using proper project structure practices demonstrates awareness of scalability needs.

Review commit history for meaningful commit messages and regular check-ins. Sporadic commits with vague messages like "fixes" or "updates" suggest poor development discipline.

Code Documentation and Comments

Evaluate documentation quality at both macro and micro levels. The codebase should include a comprehensive README explaining setup, dependencies, and basic architecture decisions.

Inline comments should explain business logic, not obvious code syntax. Complex algorithms and integration points need clear explanations. Missing documentation isn't necessarily a red flag for early startups, but complete absence suggests technical debt accumulation.

Testing Coverage and Strategy

Examine the testing strategy, recognizing that pre-Series A startups often have limited test coverage. Look for tests covering core business logic and critical user flows rather than comprehensive coverage.

Check for different testing levels: unit tests for business logic, integration tests for API endpoints, and end-to-end tests for critical user journeys. Automated testing strategies become crucial as teams scale.

Architecture Scalability Review

Technology Stack Evaluation

Assess whether the chosen technology stack aligns with business requirements and team expertise. The stack should support anticipated growth without requiring complete rewrites.

Evaluate database choices, considering both current needs and future scaling requirements. A startup handling user-generated content might struggle with a simple SQLite setup but could justify the choice for rapid prototyping.

Review third-party dependencies for stability, maintenance status, and licensing issues. Excessive dependencies on unmaintained packages create future technical debt. Understanding MVP tech stack tradeoffs helps evaluate these decisions.

Database Design and Performance

Examine database schema design for normalization, indexing, and query optimization. Early-stage startups often have suboptimal database designs, but the structure should support basic performance requirements.

Look for proper indexing on frequently queried columns and reasonable query patterns. Check for N+1 query problems and missing database constraints that could cause data integrity issues.

Evaluate backup and recovery procedures. Even early startups need basic data protection measures.

API Design and Integration Points

Review API design for consistency, versioning strategy, and error handling. Well-designed APIs indicate thoughtful architecture planning.

Check authentication and authorization implementation across API endpoints. Look for proper rate limiting and input validation. Security vulnerabilities in API design create significant technical debt.

Assess third-party integrations for error handling, retry logic, and fallback mechanisms. Brittle integrations cause operational headaches as the company scales.

Security Practices Audit

Authentication and Authorization

Evaluate user authentication implementation, looking for industry-standard practices like password hashing, session management, and multi-factor authentication options.

Review authorization logic to ensure proper access controls. Check for common vulnerabilities like insecure direct object references or missing authorization checks on sensitive endpoints.

Examine how API keys, database credentials, and other secrets are managed. Hardcoded secrets in source code represent serious security risks.

Data Protection and Privacy

Assess data encryption practices for both data at rest and in transit. Check SSL/TLS implementation and certificate management.

Review data collection and storage practices for compliance with relevant privacy regulations. Early startups often overlook privacy requirements until later stages.

Evaluate logging practices to ensure sensitive data isn't inadvertently logged. Proper log management becomes critical for debugging and compliance.

Infrastructure Security

Examine deployment and infrastructure security practices. Check for proper network segmentation, firewall configurations, and access controls.

Review monitoring and alerting systems for security events. Early detection of security issues prevents major incidents.

Assess backup security and disaster recovery procedures. Data breaches during recovery operations create additional liability.

Team Processes and Development Workflow

Version Control and Collaboration

Evaluate version control practices, including branching strategies, code review processes, and merge policies. Look for evidence of collaborative development rather than single-developer workflows.

Check for automated checks on pull requests, including linting, testing, and security scanning. These practices indicate process maturity.

Review how the team handles hotfixes and emergency deployments. Proper procedures prevent production issues during crisis situations.

Deployment and DevOps Practices

Assess deployment automation and infrastructure as code practices. Manual deployment processes create operational risk as teams grow.

Evaluate monitoring, logging, and alerting systems for production applications. Teams need visibility into application performance and error rates.

Review rollback procedures and deployment validation processes. The ability to quickly revert problematic deployments reduces operational risk.

Knowledge Management and Documentation

Examine how technical knowledge is shared and documented within the team. Look for runbooks, architecture decision records, and onboarding documentation.

Assess the team's approach to technical debt tracking and prioritization. Understanding technical debt evaluation helps gauge long-term sustainability.

Review incident response procedures and post-mortem practices. Teams that learn from failures demonstrate operational maturity.

Common Red Flags and Deal Breakers

Critical Security Vulnerabilities

Hardcoded credentials, SQL injection vulnerabilities, or missing authentication on sensitive endpoints represent deal-breaking security issues. These problems require immediate attention and significant remediation effort.

Poor data handling practices, especially for sensitive user information, create compliance and liability risks that could impact funding or partnerships.

Architectural Limitations

Monolithic architectures with tight coupling between components may prevent scaling without major rewrites. While not always deal breakers, these limitations affect growth trajectory and technical hiring needs.

Database designs that can't handle anticipated user growth create bottlenecks that require expensive migrations. Early architectural decisions have long-term consequences.

Team Process Gaps

Lack of version control, absence of code review processes, or single points of failure in technical knowledge indicate team maturity issues. These problems compound as teams grow.

Missing deployment automation or monitoring systems create operational risks that affect product reliability and team productivity.

Next Steps After Technical Due Diligence

Document findings in categories: critical issues requiring immediate attention, medium-term technical debt, and recommendations for future development.

Work with the startup team to create remediation timelines for critical issues. Factor remediation costs and timelines into investment decisions.

Consider technical advisory support or fractional CTO guidance to address identified gaps. Early-stage startups often benefit from experienced technical leadership during rapid growth phases.

Use due diligence findings to inform post-investment technical roadmap planning and hiring priorities. Technical due diligence insights guide resource allocation decisions throughout the investment lifecycle.