Technical Due Diligence for Investors

The new investor question

“Before we write the check, we’d like to bring in a technical assessor.”

This question is becoming standard in VC and M&A deals. More investors are hiring independent technical consultants to evaluate the technology, team, and architecture of companies they’re considering funding.

If you’re raising capital, you need to be ready for this. Not because your tech is bad - because unprepared founders fail technical DD even when their product is solid.

The five dimensions

1. Architecture maturity

Investors want to know whether you have a prototype or a production system - and whether the architecture supports the scale you’re promising.

What they look for:

• How data flows through the system
• Whether the architecture matches the stage (monolith is fine for early stage; over-engineered microservices for a 3-person team is a red flag)
• How the system handles failure (error handling, fallbacks, monitoring)
• Whether there’s a deployment pipeline, staging environment, and rollback capability

What kills the deal:

• A “production” system that requires manual deployment
• No monitoring or alerting
• Architecture designed for a scale that doesn’t exist yet (premature optimization)
• A single server that runs everything (including the database)

2. Team capability

Investors assess whether the team can execute the roadmap. They’re not evaluating individual skill - they’re evaluating whether the collective team matches the problem.

What they look for:

• Have team members shipped similar systems before?
• Is there a technical leader who can communicate with non-technical stakeholders?
• Does the team have the relevant domain expertise, or are they learning on the job?
• What’s the bus factor - how many people can keep the system running if one person leaves?

What kills the deal:

• The AI system was built by one person who’s the only one who understands it
• Team experience doesn’t match the problem (two junior developers building a distributed AI platform)
• No one can explain the technical decisions in plain language
• Key team members are planning to leave after the funding

3. Code quality

Investors don’t read your code line by line. They look for signals that indicate whether the codebase is healthy or a maintenance disaster waiting to happen.

What they look for:

• Test coverage (not 100%, but meaningful tests for critical paths)
• Code organization - can a new developer understand the structure
• Dependency management - how many third-party packages, are they maintained
• Documentation - is there any, or is the knowledge in people’s heads

What kills the deal:

• No tests at all for revenue-critical paths
• A 100,000-line file that “does everything”
• Dependencies on unmaintained packages (security risk)
• No documentation beyond code comments written a year ago
• Hardcoded credentials, API keys, or database URLs in the codebase

4. Dependency risk

Investors are increasingly wary of startups that are dependent on a single vendor, API, or platform that could change pricing, terms, or availability.

What they look for:

• Are you locked into a single AI vendor (OpenAI, Anthropic)?
• Can you switch if pricing changes significantly?
• Is your data stored in a system you control?
• What happens if your cloud provider has an outage?

What kills the deal:

• The entire product is a thin wrapper around GPT, with no proprietary data or technology
• No fallback plan if the AI API goes down
• Data is stored in a third-party system with no export capability
• A single cloud provider with no multi-region backup

5. Security posture

In an era of increasing regulation (EU AI Act, GDPR, CCPA), investors need to know you’re not carrying existential security risk.

What they look for:

• Authentication and authorization practices
• Data encryption (at rest and in transit)
• PII handling and data retention policies
• AI-specific risks (prompt injection, data leakage)
• Compliance documentation for relevant regulations

What kills the deal:

• Customer data sent to AI APIs without anonymization
• No security review of the AI system
• No incident response plan
• “We’ll handle compliance later” - especially for EU AI Act or GDPR

How to prepare

Before they ask

Document your architecture. One diagram, updated quarterly. Data flow, system boundaries, deployment infrastructure. If you can’t draw it, you don’t understand it well enough.

Document key technical decisions. Why did you choose this database? Why this AI model? Why this architecture? A decision log that explains your reasoning is worth more than perfect code.

Identify dependencies. List every third-party service, API, and vendor. For each: what happens if they double their price, go down for 24 hours, or discontinue the service.

Run a pre-DD audit. Hire an independent technical assessor before the investor does. It’s better to discover and fix problems yourself than to have an investor’s assessor discover them.

During due diligence

Be transparent about what you don’t know. “We haven’t addressed X yet, here’s our plan” is better than “we have that covered” - until they discover you don’t.

Bring a technical person who communicates well. The assessor will want to talk to someone who can explain the architecture. If your CTO is hands-off or your lead engineer can’t explain things to non-technical people, the assessor will flag it.

Show your documentation. A documented system signals maturity. An undocumented system that the team can explain verbally signals risk.

The preparation checklist

• Architecture diagram (current state, not aspirational)
• Decision log for key technical choices
• Dependency map with fallback plans
• Test coverage report for critical paths
• Security review documentation
• Compliance classification (EU AI Act, GDPR)
• Team capability matrix vs. roadmap requirements
• Deployment and incident response documentation

If you don’t have these, start building them now. Technical DD is no longer optional - it’s part of the fundraising process.

FAQ

When should I start preparing for technical due diligence? As soon as you start fundraising. The documentation takes 2-4 weeks to prepare and should be updated as your system evolves. Don’t wait for the term sheet.

What if we fail technical due diligence? It’s not the end of the deal - it’s a negotiating point. The investor may ask for a technical audit as a condition of funding, or they may adjust the valuation. A transparent response (“we identified these issues and here’s our plan to fix them”) is better than trying to hide problems.

Do I need a separate technical DD consultant? If the investor brings their own, you may want one too - to represent your side and ensure fairness. If they’re not bringing one, consider hiring one anyway to prepare you. The cost (€5-15K) is small relative to the deal size.