Technical Due Diligence: What Investors Actually Look For (And How to Prepare)

Most CTOs think of technical due diligence as something that happens to them. It arrives in your calendar as a meeting request from someone you've never met, with a list of data room requirements that your internal wiki definitely doesn't cover. The truth is that technical DD is something you prepare for, and the difference between "minor findings" and a 20% valuation haircut is almost always down to preparation, not the quality of your code. This post covers what investors actually look for, how the process runs, and what you can fix before they arrive.

Key Takeaways

• Technical issues found in due diligence can reduce a startup's valuation by up to 20%, and 60% of investment deals are delayed or fall through because of problems uncovered in a technical review (Sphere Inc, 2024).
• Security posture and team structure are the two categories investors flag most frequently, not just codebase quality.
• Meaningful preparation requires at least 90 days before a round. A 2-week scramble produces a data room, not readiness.

What Is Technical Due Diligence and What It Isn't

Technical DD is an investigation of your engineering organisation on behalf of an investor or acquirer. According to Codacy's 2024 guide, it covers at minimum: codebase quality, system architecture, technical debt inventory, security posture, team structure and capability, development process, and infrastructure reliability. It's not a code review. A code review inspects implementation. Technical DD asks whether the whole system, technical and organisational, is investable. Most investors expect to find some debt. The question is whether you know what you have and have a credible plan for it.

From practice: The most common misunderstanding I see at Series B companies is the assumption that DD is primarily a code quality audit. At Scout24, the first thing our external reviewers asked for wasn't the codebase, it was our incident history and our on-call rotation. Founders who've polished the code but can't answer basic questions about operational reliability are the ones who end up in difficult conversations about findings.

Who Does Technical Due Diligence?

The reviewer is typically one of three things: a specialist technical DD firm (Human Renaissance, Codacy, MEV), a technical partner at the VC who leads the review themselves, or an independent advisor brought in for a specific deal. For late Series A or Series B and above, the process almost always involves at least one external specialist, someone who isn't a stakeholder in whether the deal closes.

Duration is typically 2–4 weeks for a Series B/C review, though some acquirers run longer engagements for complex targets. The process follows a predictable structure: data room access and document review; codebase walkthrough and static analysis; technical interviews with the CTO and key engineers; infrastructure, security, and compliance review; findings synthesis and classification.

The output is a report, usually red/amber/green by category, that goes to the investment committee. You rarely see the full report. You'll see the findings your investor chooses to share as part of the negotiation.

What Do Investors Actually Look For?

In 2025, Human Renaissance's M&A Technology Due Diligence Benchmarks found that 74% of target codebases contained high-risk vulnerabilities, up from 48% two years earlier. Investors have noticed. The bar for what constitutes an acceptable finding has risen. Here's what's being evaluated across the seven core categories.

1. Codebase health. Is the code maintainable by people who didn't write it? Reviewers look at test coverage, documentation quality, automated quality gates in CI, and the ratio of code that's been touched recently versus code nobody dares modify. A codebase where more than 30% of files haven't been changed in over a year is a flag. That's either dead code or code with hidden dependencies that would break if anyone tried to refactor it.

2. Architecture decisions. Is the architecture appropriate for your current scale and your projected growth trajectory? Reviewers look for critical single points of failure, undocumented architectural decisions, and the gap between what the CTO says the architecture is and what it actually is. A well-maintained ADR (Architecture Decision Record) log signals maturity here more than any individual decision does.

3. Technical debt inventory. This is less about how much debt you have and more about whether you know. Companies that can produce a categorised, prioritised debt backlog, with rough time estimates, come across very differently from companies that hand-wave at "yeah, we have some debt." Investors aren't expecting perfection. They're expecting self-awareness and a plan.

4. Security posture. Secrets management, dependency scanning, access controls, incident response documentation, and GDPR compliance for EU companies. For any company handling personal data under European jurisdiction, GDPR readiness is now a standard line item in technical DD. Reviewers check not just whether you have a privacy policy but whether your data retention practices, subprocessor documentation, and breach notification process are defensible.

5. Development process. How does your team actually ship? Deployment frequency, functioning on-call rotation, sprint cadence, and the process for making architectural decisions. A team that ships daily with monitored deployments tells a fundamentally different story than a team that does monthly releases with manual steps.

6. Team structure and capability. Are there key-person dependencies? Can the engineering team execute without any single individual? Reviewers look at the distribution of institutional knowledge, the presence (or absence) of an engineering management layer, recent turnover patterns, and whether the CTO is a bottleneck for every significant technical decision.

7. Infrastructure and reliability. Uptime history, incident frequency, mean time to recovery, cloud cost trajectory against revenue. A startup where infrastructure costs are growing faster than revenue is a yellow flag even if no single incident looks catastrophic.

Technical issues discovered during due diligence affect valuations and deal terms in the majority of transactions. In a 2024 study by Sphere Inc, nearly 60% of investment deals were delayed or fell through because of problems uncovered in a technical review. Investors have adapted by building technical screening earlier in the process, meaning findings that once came up at term sheet stage now surface at first-meeting stage for tech-forward funds.

12-month DD preparation plan

How Does Technical Debt Affect Valuation?

In 2024, Allied Venture Partners found that companies entering due diligence with unacknowledged technical debt faced valuation reductions of up to 20% and, in some cases, post-investment remediation costs 3–5x higher than if the issues had been disclosed and priced upfront. Not all debt is equal, and knowing the difference is the first thing you need to communicate clearly.

There are three meaningful categories:

Strategic debt is a deliberate trade-off. You shipped a feature in four days instead of four weeks by skipping automated tests. You knew the trade-off. You documented it. You plan to address it in Q3. Investors can work with this. It demonstrates judgment.

Accidental debt is the kind nobody planned. It accumulates silently, dependency versions that stopped getting updated, a microservice that expanded beyond its original scope, a database schema designed for version one of the product that's now doing triple duty. This is also manageable if you can name it, estimate it, and show it's on a plan.

Liability debt is actively risky: security holes that remain open, systems with no documented owner, unmaintainable code that's also handling financial transactions, or compliance gaps that expose the company to regulatory action. This is the category that reduces valuations. It's not that it exists, it's that companies with liability debt often don't know where it is.

From practice: The debt category that surprises investors most isn't poor test coverage, it's what I'd call "orphaned infrastructure." At multiple companies I've worked with, there have been production services running in cloud accounts that senior engineers can't fully explain. Often these trace back to a former employee or a one-week prototype that somehow became load-bearing. Nobody documented it because nobody meant to keep it. When a DD reviewer finds a service with no owner, no runbook, and meaningful traffic hitting it, that's an immediate red flag, not because the code is bad, but because it signals a fundamental gap in operational hygiene.

What Engineering Team Issues Get Flagged?

Team issues are often more concerning to investors than code quality. A codebase can be refactored. A team with structural problems is much harder to fix post-close. According to a 2024 CB Insights analysis of 483 startup failure post-mortems, 23% cited not having the right team as a primary cause of failure and investors have learned to look for early structural signals before that failure mode develops.

The flags reviewers look for specifically:

Key-person dependency. One engineer who "knows everything" about a critical system and shows any sign of being a flight risk. It doesn't have to be someone who's threatening to leave, it's enough that they hold knowledge nobody else has. Reviewers check this by asking engineers directly: "What would break if X left tomorrow?"

No engineering management layer past 15 people. A team of 20 engineers reporting directly to a CTO is a structural problem, not just a management style. It means the CTO is a bottleneck for every people decision and that the team has no middle layer to absorb growth.

High recent turnover, especially senior engineers. Two or three senior engineer departures in the six months before a round are a red flag regardless of the stated reasons. Reviewers know that people leave before they say they're unhappy, and departure clustering at the senior level is a signal about management quality, compensation, or technical culture.

The team can't ship without the CTO present. This comes up in technical interviews. If every significant deployment decision traces back to one person, that's a scalability risk the investor is buying.

The Due Diligence Timeline: What Happens When

Knowing the timeline lets you use it. Here's what a typical Series B review looks like across four weeks.

Week 1: Data room and architecture. Reviewers work through your data room: architecture diagrams, infrastructure documentation, security policies, incident history, team org chart, and any existing technical debt documentation. They run static analysis on the codebase or request a walkthrough. The goal is to form a hypothesis about where the problems are before they start asking questions.

Week 2: Technical interviews. Sessions with the CTO, 2–3 senior engineers, and ideally the engineering lead if that's a separate role. These aren't adversarial. They're trying to understand how decisions get made, how incidents get handled, and whether the technical direction makes sense for the business. How you answer questions about technical debt matters as much as what you say about it.

Week 3: Synthesis. The reviewer compiles findings and classifies them red/amber/green. Red = deal risk or valuation impact. Amber = requires a mitigation plan. Green = no material concern. This is where they decide what goes in the report and how it's framed.

Week 4: Report and management response. The report goes to the investment committee. You're typically invited to provide a management response, a written reply to each finding that either acknowledges it with a remediation plan or disputes it with evidence. This is not optional, and it's not a formality. A well-written management response that shows self-awareness and a credible plan regularly converts amber findings into green ones.

The management response is underused. Most founders treat it as a defensive document. The better approach is to treat it as an opportunity to demonstrate exactly the kind of engineering maturity that investors want to see, here's what we found, here's when we're fixing it, here's how we'll know it's done.

what a fractional CTO does

Common Red Flags That Kill or Delay Deals

These aren't hypothetical. They're the six findings that most consistently either kill deals outright or force a valuation renegotiation.

1. No documentation of architecture decisions. If there's no ADR log or equivalent, it means architectural choices were made informally and can't be reviewed or defended. Reviewers interpret this as: "this team doesn't think about consequences."

2. Secrets ever committed to git. Even if rotated. A git history containing API keys, database credentials, or private keys, even ones that were removed and rotated after the fact, tells reviewers that your secret management practices weren't in place when it mattered. This is one of the few findings that's hard to explain away.

3. No automated testing in a CI pipeline. Not zero test coverage, no automated gate at all. If every deployment is a manually checked step, your velocity and reliability claims are structurally unsupported. This is a red finding at any stage above pre-seed.

4. Key engineer departure in the 6 months before the round. Especially if that person was the main author of a critical system. Reviewers will ask about it. If you can't give a credible account of knowledge transfer, it stays red.

5. Unacknowledged security incidents. A security incident on its own isn't a deal-killer, how you handled it often is. Incidents that were discovered by a third party, not disclosed, or responded to with "we fixed it and moved on" without any process change are the problem. Reviewers are looking for whether you learned from it.

6. Cloud infrastructure cost growing faster than revenue. Unit economics are a technical concern, not just a financial one. A cloud bill that's scaling 2x for every 1.2x of revenue growth is a signal about architectural decisions and about whether the team is paying attention to efficiency. This one is easy to miss internally because it creeps up gradually.

From practice: The finding that most consistently surprises founders is number three. The absence of any automated testing gate in CI. It's common enough that I check for it specifically in every engagement. The usual explanation is "we were moving too fast." The problem is that's exactly what a DD reviewer hears as confirmation that quality was deprioritised, not as context. A three-line GitHub Actions job that runs a lint check and a single smoke test is better than nothing, it signals intent. I've seen this single change turn a red finding amber.

The Seller-Side Checklist: 15 Things to Verify Before Investors Arrive

Work through this list at least 90 days before you expect a technical review. Not two weeks before.

1. ADR log exists and covers the last 12 months of significant architectural decisions.
2. Secret scanning has been run across your full git history, not just HEAD, and any found secrets rotated and documented.
3. Test coverage baseline is measured and known. Even if it's 18%. Know the number.
4. A CI pipeline runs on every pull request, with at minimum linting, a build check, and one automated test suite.
5. Dependency audit has been run (Dependabot, Snyk, or equivalent) and critical/high CVEs are resolved or have a documented exception.
6. Up-to-date architecture diagram reflecting the actual production state, not the version from two years ago.
7. Incident history summary covering the past 12–24 months: what happened, how it was detected, how long it took to resolve, what changed as a result.
8. On-call rotation is documented and includes more than one or two people.
9. Team org chart with tenure and system ownership mapped, who owns what, and who is the backup if they leave.
10. GDPR Data Processing Agreement and subprocessor list are current if you operate under EU jurisdiction.
11. Data retention policy exists and reflects what's actually implemented.
12. Cloud cost dashboard is active with monthly spend trends available and explainable.
13. Access control audit completed, former employees removed from systems, MFA enforced on production access.
14. Deployment process is documented end to end, including rollback steps.
15. Technical debt backlog exists, even a rough one, categorised by priority and with rough effort estimates.

platform engineering playbook

Frequently Asked Questions

How early should I start preparing for technical due diligence?

Start 90 days before you expect a term sheet. Most founders start two weeks before and end up in reactive mode, patching surface-level issues rather than addressing the structural ones reviewers actually focus on. The three-month window gives you time to close real gaps: test coverage, dependency audits, ADR documentation, and incident history. In 2024, Kruze Consulting's VC due diligence survey found that companies that prepared a structured technical data room at least 60 days in advance saw significantly fewer material findings during formal review.

What's in a technical data room?

A technical data room typically includes: an architecture overview document, infrastructure diagrams, a system inventory, your incident history (12–24 months), on-call runbooks, team org chart with system ownership, dependency and security scan results, GDPR and compliance documentation, current technical debt backlog, and deployment process documentation. Some investors also request access to your CI metrics, deployment frequency, lead time, change failure rate, and mean time to recovery. These four metrics (from the DORA framework) have become standard in more technically sophisticated due diligence processes.

Can we fail technical DD and still close the round?

Yes. Technical DD rarely kills a deal outright, it prices it. Significant findings become negotiation leverage: a lower valuation, a post-close remediation plan with milestones tied to a tranche of funding, or representations and warranties in the term sheet. What causes deals to fail is not findings themselves but founders who respond to findings defensively, dispute them without evidence, or can't demonstrate awareness of their own technical situation. The deal failure rate from technical findings is highest when there's a credibility gap. When what you told investors in earlier conversations doesn't match what the reviewer found.

How do I talk about technical debt in the DD process?

Directly and specifically. The worst thing you can do is deflect or minimise. Say what you have, say how much it costs you in engineering time, and say what you're doing about it. If you're spending 30% of your sprint capacity on legacy system maintenance and you're not doing anything about it, say that and explain why it's been a trade-off. Investors are evaluating your judgment as much as your code. "We have X, we know it costs us Y, we're addressing it with Z over 6 months" is a better answer than "we move fast, all startups have debt."

Does every VC firm do technical DD?

Not all, and not equally. Pre-seed and seed stage funds typically don't run formal technical reviews. The team and market matter more at that stage than architecture decisions. At Series A, it varies by fund: some run a two-day technical partner review, others rely on a reference call with a technical advisor. By Series B, technical DD is standard and usually involves at least one external specialist. For M&A transactions at any stage, a full technical review is expected. If you're fundraising at Series A and haven't been asked technical questions, that's worth noting, either the fund isn't technically rigorous, or they're deferring the conversation to later.

What does GDPR compliance look like for EU startups in a DD context?

For any company handling personal data under EU jurisdiction, reviewers look for four things: a current Data Processing Agreement with each subprocessor, a data retention policy that reflects what's actually implemented (not just documented), a documented process for handling Data Subject Access Requests, and evidence that your breach notification process has been tested. The bar isn't perfection, it's demonstrability. Can you show that your GDPR posture is managed rather than ignored? One finding that regularly surprises EU startups: if you're using US-based SaaS tooling (analytics, CRM, email platforms) for EU customer data, you need current Standard Contractual Clauses or equivalent transfer mechanisms in place. Many Series A companies haven't done this.

Conclusion

Technical due diligence is an opportunity disguised as an inspection. The companies that come through cleanest aren't the ones with the least debt. They're the ones that ran the process on themselves first. They know where their risks are, they can name them, and they've thought about what to do about each one. That's the posture investors are looking for.

The preparation work isn't complicated. It's a 15-item checklist, 90 days of lead time, and the discipline to treat it as a serious operational exercise rather than something you'll sort out when the term sheet arrives. For most CTOs, the gap between "minor findings" and "20% valuation haircut" isn't technical quality, it's organisational self-awareness.

If you're preparing for a round and want to run a seller-side technical review before investors arrive, book a call to talk through where you are and what would give you the most coverage.