Technical Due Diligence: What Investors Look For

Technical due diligence can make or break a funding round. Understanding what investors examine — and why — gives founders a realistic picture of their startup's technical health long before external scrutiny begins.

Raising a Series A brings a new kind of scrutiny. While founders focus on growth metrics, product roadmap, and team composition, technical due diligence runs quietly in the background — and it can derail deals that otherwise look promising. An investor's technical consultant doesn't care about what the product does. They care about whether the underlying system can sustain the business as it scales.

Many founders are caught off guard. The codebase that shipped an MVP in eight weeks — the one that helped close a seed round on traction alone — can look very different under the lens of a formal technical audit. Shortcuts made to hit launch milestones become documented liabilities. Architecture decisions made without a senior engineer are questioned against industry standards. Security practices that never surfaced as a problem suddenly represent existential risk.

This guide covers what technical due diligence actually involves, the seven areas investors examine most closely, the red flags that most commonly surface, and a structured framework for preparing before the audit begins.

What Technical Due Diligence Involves

Technical due diligence (TDD) is a systematic assessment of a company's technology, engineering practices, infrastructure, and technical team. For most Series A rounds — and increasingly at seed stage for deep-tech or B2B SaaS companies — investors commission this assessment before closing the round.

Who Conducts It

Investors rarely conduct technical due diligence themselves unless the fund has a dedicated engineering partner. More commonly, the review is carried out by:

• External engineering consultants — specialised firms or senior engineers hired specifically for due diligence engagements
• The investor's technical advisor — a trusted CTO or senior engineer in the investor's network
• A portfolio company CTO — someone already known to the investor who can assess the technology objectively
• The fund's in-house engineer — present at larger venture funds with dedicated technical teams

The reviewer's background shapes what they focus on. A consultant from a security firm will weight vulnerability findings differently than a product-focused engineering advisor. Founders should ask who is conducting the review and what their background is — this is a reasonable question and helps calibrate the preparation focus.

When It Happens

Technical due diligence typically begins after a term sheet is signed and before the round closes. For most Series A processes, this means a 4-6 week window between term sheet and close, with TDD running in parallel with legal due diligence.

At seed stage, formal TDD is less common — but due diligence-lite conversations happen regularly. Seed investors often ask technical founders to walk through their architecture, or request a code sample review. Non-technical founders raising seed rounds should expect technical questions even without a formal audit.

What Access They Request

A standard technical due diligence request typically includes:

• Read-only access to the main code repositories (GitHub, GitLab, Bitbucket)
• Architecture diagrams and technical documentation
• Infrastructure diagrams and cloud provider dashboards (read-only)
• CI/CD pipeline configuration
• Dependency manifests (package.json, requirements.txt, Gemfile, etc.)
• Security scan results or penetration test reports (if they exist)
• One or two technical team interviews
• Access to staging environment for exploratory testing

Technical due diligence doesn't test whether your code works — it tests whether your code is safe, sustainable, and scalable enough to be worth investing in.

Why Technical Due Diligence Can Affect Your Valuation

Technical findings don't always kill deals outright. More commonly, they shift the terms. Understanding the spectrum of outcomes helps founders calibrate their preparation effort.

The Spectrum of Outcomes

Technical due diligence findings typically lead to one of five outcomes:

1. Clean review, full terms maintained — No material issues. Deal closes as negotiated.
2. Minor findings, acknowledged and accepted — Issues are noted, both parties agree they're manageable, deal closes with no change.
3. Remediation conditions added — Certain issues must be addressed post-close, often within a defined timeframe. Common for medium-severity technical debt.
4. Valuation adjustment — Significant technical issues reduce the effective valuation, either through price reduction or by increasing the investor's equity stake.
5. Deal collapse — Critical issues (data breach liability, unresolvable IP conflicts, catastrophic architecture) cause the investor to withdraw.

Why Investors Price Technical Risk

Investors price technical due diligence findings because technical risk directly translates to business risk. Three dimensions matter most:

Scalability risk: If the current architecture can't support 10x the current load, growth will require a costly rebuild. That rebuild takes 6-18 months, consumes engineering resources, and delays feature development. Investors model this cost into their expected returns.

Security and liability risk: A startup holding customer data that has unencrypted databases, no access controls, or known vulnerabilities represents potential regulatory and legal liability. Under GDPR and the Australian Privacy Act, data breaches carry significant financial penalties. Investors are acquiring that liability when they invest.

Key-person risk: If the entire system is understood by one engineer, the company's technical operations depend entirely on retaining that person. Investors view this as a concentration risk equivalent to having one customer represent 80% of revenue.

Most founders fail technical due diligence not because their product is broken, but because they cannot prove it isn't.

The Seven Areas Investors Examine

1. Code Quality and Architecture

Reviewers assess whether the codebase reflects deliberate decision-making or accumulated chaos. The goal isn't to find perfect code — it's to distinguish intentional shortcuts from structural problems.

Key questions the reviewer is asking:

• Is the codebase readable and navigable by a new engineer?
• Are architecture decisions documented and explainable?
• Is there consistency across modules, or does the code look like it was written by five different teams with no coordination?
• Are database schemas normalised appropriately? Are there signs of uncontrolled schema drift?
• Is there evidence of active refactoring, or has the codebase only grown outward?

Early-stage codebases are not expected to match enterprise standards. Reviewers calibrate their expectations to the company's stage and funding history. A two-year-old, bootstrapped company is assessed differently than a company raising its second institutional round.

2. Security and Data Protection

Security is the highest-stakes area of technical due diligence. Issues here can trigger deal collapse regardless of how strong the rest of the review is.

Reviewers look for:

• Credentials management: No hardcoded API keys, passwords, or secrets in the repository. Secrets should be stored in a secrets manager or environment variables, not committed to version control.
• Authentication and authorisation: Proper implementation of login, session management, and access control. Role-based access control where appropriate.
• Encryption: Data encrypted at rest and in transit. Databases using encryption-at-rest. All APIs served over HTTPS.
• Dependency vulnerabilities: Dependencies scanned for known CVEs. Automated scanning (Dependabot, Snyk, or similar) in place.
• Privacy compliance: Evidence that data collection, storage, and deletion align with applicable privacy legislation. A privacy policy that matches actual data practices.

3. Scalability and Performance

Investors are not buying the current product — they are buying the product at 10-50x current scale. Technical due diligence evaluates whether the architecture can support that growth, and what it would cost to get there.

Key assessment dimensions:

• Database design: Are indexes in place? Is the data model designed for query patterns at scale? Are there N+1 query problems?
• Infrastructure elasticity: Is the infrastructure designed to scale horizontally? Are there single-instance bottlenecks?
• Caching strategy: Is there evidence of appropriate caching at the application and database layer?
• Load testing: Has the system been tested under realistic load? Are results documented?
• Background job architecture: Are long-running processes properly queued and retried? Or do they run synchronously in the web request cycle?

4. Technical Debt Assessment

Technical debt is universal. Every codebase has it. Reviewers are not looking for zero technical debt — they are looking for a team that is aware of it, has it under control, and is making deliberate decisions about when to address it.

The assessment covers:

• Dependency health: Package versions, frequency of updates, and whether outdated dependencies are tracked.
• Test coverage: Not just line coverage percentages, but the quality of tests. Unit tests, integration tests, and end-to-end tests for critical paths.
• Dead code and abandoned modules: Evidence of incomplete features, commented-out code at scale, or abandoned experimental paths.
• Known issues tracking: Is there an active backlog of technical debt items? Are they prioritised?

Reviewers distinguish between intentional debt — shortcuts made knowingly to ship faster — and unintentional debt that accumulated through neglect. The former signals maturity; the latter signals risk.

5. Development Practices and Workflows

Engineering velocity and quality depend on consistent practices. Reviewers examine whether the team has the operational foundations to sustain and accelerate development.

Key areas:

• Version control hygiene: Branching strategy, commit message quality, pull request process, protected main/production branches.
• CI/CD pipeline: Automated testing on every commit or pull request. Automated deployment to staging, ideally to production.
• Code review process: Evidence that code is reviewed before merging. Code review standards and expectations are defined.
• Environment management: Separation between development, staging, and production environments. Production-like staging environments.
• Incident response: Is there evidence of how the team handles outages? Post-mortems, runbooks, or monitoring dashboards.

6. Intellectual Property

IP issues can surface late in due diligence and be difficult to resolve quickly. Reviewers and legal teams check:

• Open-source license compliance: Dependencies that carry GPL or AGPL licenses can create IP obligations that affect the investability of the company. An audit of open-source license types in the dependency tree is standard practice.
• Employee and contractor IP agreements: Every engineer who wrote production code should have a signed IP assignment agreement. Missing agreements — especially from early contractors — are common and problematic.
• Prior employer IP: Founders and early engineers should not have built core systems using methodologies, algorithms, or designs they developed for a previous employer without explicit clearance.
• Third-party data usage: If the product uses data scraped from third-party sources or incorporates third-party APIs, the terms of service for those sources are reviewed.

7. Team and Knowledge Distribution

The technical team itself is part of due diligence. Investors are assessing not just what has been built, but the team's ability to maintain, extend, and operate it.

Key risk factors:

• Bus factor: How many engineers would have to leave before the technical operations of the company are at serious risk? A bus factor of 1 — a single person who understands the entire system — is a significant red flag.
• Documentation quality: Can a new engineer onboard within a reasonable timeframe? Is there a README that accurately describes how to set up the development environment? Is the architecture documented?
• Key person interviews: Technical leads are typically interviewed. Reviewers assess technical depth, decision-making quality, and whether the engineer can articulate their decisions clearly.
• Team coverage: Does the team have the skills required to operate the system? Are there critical skill gaps that would need immediate hiring?

Common Red Flags That Kill Deals

The following issues most frequently surface in Series A technical due diligence and have the highest probability of materially affecting deal terms or triggering further scrutiny.

A 90-Day Preparation Framework

The most effective approach to technical due diligence preparation is treating it as a standing practice rather than a pre-fundraise sprint. Startups that maintain strong engineering hygiene throughout their lifecycle face significantly less disruption when due diligence arrives.

For founders who haven't yet established these practices, a 90-day preparation window is realistic for most Series A-stage companies.

Days 1–30: Audit and Triage

• Security scan of the full git history. Run truffleHog or equivalent to identify any committed secrets. Rotate any exposed credentials immediately.
• Dependency audit. Run npm audit, pip check, or equivalent. Identify and categorise all critical and high severity vulnerabilities.
• Open-source license audit. Use FOSSA, license-checker, or equivalent to identify all open-source licenses in the dependency tree. Flag any copyleft licenses (GPL, AGPL, LGPL).
• IP agreement audit. Compile a list of every engineer, contractor, and consultant who wrote production code. Verify signed IP assignment agreements for each. Engage a lawyer to remediate any gaps.
• Test coverage baseline. Measure current test coverage. Identify the most critical user paths with zero coverage.
• Documentation inventory. List what architectural, operational, and onboarding documentation exists. Identify the largest gaps.

Days 31–60: Remediation Priorities

Not all issues are worth fixing before due diligence. The goal is to address the highest-risk items — those most likely to trigger valuation adjustments or deal conditions — and to document everything else as a known, managed backlog.

• Remediate critical security vulnerabilities. Address all critical and high severity dependency vulnerabilities. Migrate any hardcoded secrets to a secrets manager.
• Establish a basic CI/CD pipeline if one does not exist. Even a simple pipeline that runs tests on pull requests demonstrates process maturity.
• Write tests for critical paths. Focus on the happy paths most critical to the business: payment flows, authentication, core data operations. Aim for meaningful coverage on these before broader coverage targets.
• Implement secrets management if not in place. Migrate to AWS Secrets Manager, Azure Key Vault, HashiCorp Vault, or equivalent.
• Resolve GPL license conflicts. Replace GPL-licensed dependencies in commercial code paths. Document the decision and replacement.

Days 61–90: Documentation and Packaging

• Architecture document. A clear, up-to-date diagram and narrative description of the system architecture: services, databases, integrations, data flows, and hosting.
• Technical debt register. A documented list of known technical issues, their severity, and the team's plan for addressing them. This demonstrates control, not weakness.
• Onboarding documentation. A README and development environment setup guide that a new engineer could follow successfully without assistance.
• Security overview document. A brief summary of the security practices in place: secrets management, access control, encryption, scanning cadence.
• Infrastructure documentation. Cloud provider accounts, services in use, cost structure, and environment separation.
• Prepare the technical team for interviews. Brief the CTO or lead engineer on what to expect: questions about architecture decisions, technical trade-offs, and team knowledge distribution.

What a Clean Due Diligence Report Looks Like

A clean technical due diligence report does not mean a perfect codebase. Series A investors understand they are investing in a startup, not a mature enterprise software company. What a clean report signals is not absence of debt or shortcuts, but rather:

• Awareness and control: The team knows what their technical issues are and has a plan. They are not operating in the dark.
• No critical security liabilities: No hardcoded secrets, no known critical vulnerabilities in production, no unencrypted customer data.
• Clean IP chain of ownership: The company demonstrably owns what it has built. Agreements are in place. No GPL conflicts in commercial code.
• Sustainable engineering practices: Version control, code review, automated testing — even at a basic level — are established and used consistently.
• Honest representation of technical debt: The team can articulate what they owe, why they incurred it, and when they plan to pay it down.
• Distributed knowledge: The system does not live solely in one person's head. Documentation, commit history, and team interviews confirm this.

Investors are experienced at interpreting technical due diligence findings in context. A startup that raised $500K in seed and shipped a product with a small team is not expected to have the engineering practices of a 50-person company. What experienced reviewers look for is whether the team builds with intention, learns from failures, and can scale its practices alongside its headcount.

The fastest way to lose valuation in a Series A is to let an investor's consultant find your security issues before you do.

Preparing Before the Review Begins

Technical due diligence is most manageable when it is treated as an ongoing hygiene practice rather than a pre-fundraise emergency. The preparation framework outlined above — audit, remediate, document — works best when started at least 90 days before going to market, but many of the foundational practices take years to establish properly.

The key areas to prioritise:

1. Resolve all high-severity security vulnerabilities and remove any secrets from version control history
2. Ensure IP assignment agreements are signed by every engineer who wrote production code
3. Audit open-source license usage for GPL conflicts
4. Establish a basic CI/CD pipeline with automated test runs
5. Document the architecture and maintain an honest technical debt register
6. Reduce bus factor by distributing knowledge and improving documentation

Founders who approach technical due diligence proactively — rather than reactively — are in a significantly stronger position to maintain deal terms, preserve valuation, and build investor confidence in the technical foundations of the business.