When a venture capital firm considers investing $5 million or more in your company, they will hire someone to look under the hood of your technology. Technical due diligence is the process by which investors assess whether your software can support the growth your business plan promises. A clean technical assessment accelerates deal closure. A problematic one can reduce your valuation by 20 to 40 percent, add onerous terms to the term sheet, or kill the deal entirely.
Most founders encounter technical due diligence for the first time during their Series A or Series B round. By then, the codebase reflects every shortcut, every midnight hack, and every deferred decision from the startup’s history. Understanding what evaluators look for, and preparing accordingly, is the difference between a smooth process and a painful one.
What the Technical Due Diligence Process Looks Like
A typical technical due diligence engagement lasts 1 to 3 weeks and involves a third-party evaluator (an independent consulting firm or a technical advisor engaged by the investor) examining your technology across six dimensions: architecture, code quality, infrastructure, team and process, security, and scalability.
The process usually begins with a questionnaire covering 50 to 100 questions about your technology stack, team structure, development practices, and infrastructure. The evaluator then reviews documentation, examines the codebase directly (read-only access to your repository), and conducts 2 to 4 interviews with your technical leadership (CTO, VP of Engineering, lead architects).
The output is a report that categorizes findings as strengths, concerns, and risks. Concerns are issues that should be addressed post-investment. Risks are issues that could materially affect the company’s ability to execute on its growth plan. A report with multiple high-severity risks will prompt the investor to negotiate a lower valuation, require a remediation plan as a condition of investment, or walk away.
Investors are not looking for perfection. They are looking for a codebase and team that can scale from the current stage to the next stage. A Series A due diligence expects startup-quality code with a credible path to maturity. A Series B due diligence expects engineering practices that can support a team growing from 10 to 50 engineers.
Architecture: Monoliths, Microservices, and Everything Between
Evaluators assess whether your architecture can handle the growth implied by your financial projections. If your business plan projects 10x user growth over 18 months, your architecture must have a plausible path to supporting that scale.
What evaluators want to see:
A clear architectural diagram showing major components, their responsibilities, and how they communicate. You would be surprised how many Series A companies cannot produce this artifact. If you do not have one, create it before due diligence begins.
Separation of concerns between data storage, business logic, and presentation. A codebase where database queries are embedded in UI components is a red flag for maintainability and scalability.
A monolithic architecture at the Series A stage is perfectly acceptable and often preferred. Evaluators are suspicious of premature microservices architectures because they add operational complexity without corresponding benefits at small scale. What matters is that the monolith is well-structured: clear module boundaries, minimal circular dependencies, and a strategy for extracting services when specific components need independent scaling.
Common red flags:
Single points of failure with no failover strategy. If your entire application runs on one server with no redundancy, evaluators will flag it as a risk.
Tight coupling to a specific vendor or technology that limits future options. A codebase that is deeply integrated with a niche database that only one engineer on the team understands is a risk.
A data model that cannot accommodate the product roadmap. If your schema assumes single-tenant data and your business plan includes multi-tenancy, the evaluator will flag the gap between architecture and ambition.
Code Quality and Technical Debt Assessment
Evaluators do not read every line of code. They sample strategically: core business logic, the most-changed files (indicating active development areas), and areas identified as problematic during interviews.
What evaluators want to see:
Test coverage above 60 percent for critical business logic, with integration tests covering major user flows. The specific number matters less than the trend: is test coverage increasing or decreasing over time? A codebase with 45 percent coverage and a clear upward trajectory is viewed more favorably than one with 70 percent coverage that has been declining.
Consistent code style enforced by automated linting and formatting. This signals that the team has established and follows engineering standards. Inconsistent formatting across files suggests a lack of code review discipline.
Reasonable dependency management. Are dependencies up to date? Are there known vulnerabilities in the dependency tree? Evaluators will run tools like npm audit, safety check (Python), or Snyk against your dependencies. A few moderate vulnerabilities are normal. Critical vulnerabilities in production dependencies are a red flag.
Documentation for architectural decisions and non-obvious business logic. You do not need comprehensive documentation for everything, but the evaluator should be able to understand why a complex piece of code works the way it does without scheduling a call with the original author.
Common red flags:
Copy-pasted code blocks across the codebase, suggesting a lack of abstraction and a higher maintenance burden.
Commented-out code blocks, dead code, or TODO comments referencing issues from 18 months ago. These signal deferred maintenance.
A Git history showing that one engineer authored 80 percent or more of commits. This “bus factor” risk means losing one person could cripple the team.
Hardcoded credentials, API keys, or environment-specific values in the codebase. This is both a security risk and a signal of immature development practices.
See also: Transitioning from Services to Product: A Strategic Guide
Infrastructure and DevOps Maturity
Evaluators assess whether your infrastructure can support reliable, repeatable deployments and handle operational incidents without heroics.
What evaluators want to see:
Infrastructure defined as code (Terraform, Pulumi, CloudFormation, or equivalent). If your production environment was set up by clicking through the AWS console and nobody documented the configuration, recreating it after a disaster is uncertain.
A CI/CD pipeline that runs tests and deploys automatically. The bar is not complex orchestration; it is that deploying to production does not require SSH access to a server and a series of manual commands.
Monitoring and alerting that covers application health, error rates, and key business metrics. At minimum: uptime monitoring, application error tracking (Sentry, Datadog, or equivalent), and alerts that reach on-call engineers within minutes.
A backup and disaster recovery strategy that has been tested. “We have automated backups” is good. “We have automated backups and we restored from them successfully on [specific date]” is what evaluators want to hear.
What evaluators understand about stage-appropriate infrastructure:
A Series A company is not expected to have a fully redundant, multi-region deployment. It is expected to have automated deployments, basic monitoring, and a recovery plan. The evaluator’s concern is not current sophistication but whether the team knows what mature infrastructure looks like and has a roadmap to get there.
Security Posture and Data Protection
Security findings in due diligence carry disproportionate weight because they represent both technical risk and legal liability. A data breach after investment directly impacts the investor’s return.
What evaluators assess:
Authentication and authorization. Are passwords hashed with bcrypt, scrypt, or Argon2 (not MD5 or SHA-256)? Is session management secure (HTTP-only cookies, secure flag, reasonable expiration)? Does the application enforce role-based access control, and is the authorization logic centralized rather than scattered across endpoints?
Data protection. Is sensitive data (PII, financial information, health records) encrypted at rest and in transit? Are database backups encrypted? Is there a data retention policy, and is it enforced programmatically?
Vulnerability management. Is there a process for tracking and remediating security vulnerabilities? How quickly were the last three critical vulnerabilities patched after disclosure? Is there a responsible disclosure policy?
Third-party risk. What third-party services have access to your data? Are those services SOC 2 compliant? Are API keys rotated regularly? Is there an inventory of all third-party integrations and the data they access?
Preparing for the security assessment:
Run a dependency vulnerability scan and remediate critical findings before due diligence begins. Conduct a basic penetration test (even a lightweight one using OWASP ZAP) and address the findings. Document your security practices in a brief security overview document. These proactive steps signal maturity and prevent the evaluator from discovering issues that you could have fixed.
Preparing Your Team for the Process
Technical due diligence includes interviews with your technical leadership, and the way your team answers questions matters as much as the technical artifacts.
Coach your team on these principles:
Be honest about technical debt. Every startup has it. Evaluators know this. What they want to hear is that you know where the debt is, you understand the risk it poses, and you have a prioritized plan to address it. Minimizing or hiding known issues destroys credibility if the evaluator discovers them independently.
Explain decisions in business context. “We chose a monolithic architecture because we needed to ship in 8 weeks and had 2 engineers” is a reasonable explanation. “We chose a monolithic architecture because it was easier” is not.
Demonstrate learning velocity. The evaluator cares less about where you are today and more about how quickly you are improving. Show that your practices have matured over the past 6 to 12 months: “We introduced automated testing 8 months ago and coverage has grown from 15 percent to 55 percent” is a strong signal.
Have your architectural diagram, a brief technology overview document, and access credentials ready before the engagement begins. A responsive, organized team makes a positive impression that influences the overall assessment.
If you have a fundraising round approaching and want to ensure your technology makes a strong impression during due diligence, talk to us. The Proper Motion Company helps startups prepare for technical due diligence with pre-assessment audits, remediation planning, and architectural documentation.