What technical due diligence really looks at

Investor readiness is about evidence, not polish: how to prepare a data room and a technical narrative that hold up.

By Elias Limouni · 12 November 2026 · 5 min read

Technical due diligence tests whether the technology can support the plan investors are backing, and whether the team understands its own risks.
Reviewers look at architecture, code and delivery, security and data protection, intellectual property, team and key-person risk, and cost.
A tidy data room helps, but a credible technical narrative, weaknesses included, matters more.
Start months before you need it. Most fixes are cheap with time and expensive under a deadline.

What diligence is really asking

Technical due diligence is often treated as an exam: a checklist to survive, a code scan to pass. Founders prepare for it as if the aim were a spotless report. Having been through it as a founder, I think that is the wrong frame, and it leads to the wrong preparation.

Diligence asks two questions. Can this technology support the plan the investor is about to back? And does this team understand its own risks? A company with visible technical debt and a clear plan for it usually fares better than one that claims to have none. Reviewers expect to find problems. What they are assessing is judgment.

What reviewers look at

The scope varies with the stage of the company and the size of the investment, but the same areas come up again and again.

Architecture and scalability How the system is put together, where it will strain as usage grows, and whether the roadmap in the investment case is realistic on this foundation.
Code and delivery Quality in the parts that matter, automated testing, how changes reach production and how often, and how incidents are handled.
Security and data protection Access control, secrets management, encryption, penetration testing, and UK GDPR: what personal data you hold, where, on what lawful basis, and who processes it for you.
Intellectual property Who wrote the code and under what agreement, open-source licences and their obligations, and whether key assets sit with the company rather than a founder or contractor.
Team and key-person risk Who knows how the system works, how much of that is written down, and what happens if one person leaves.
Cost and suppliers Hosting and third-party costs, how they scale with customers, and dependence on any one supplier or model provider.
AI, where relevant What is genuinely proprietary, how outputs are evaluated, and how customer data is used in prompts or training.

Depth varies too. An early review may be a few conversations and a look at the repository; a later one may add an external code and security assessment. Either way, the reviewer is building a picture of risk, and every area feeds the same question: what could stop this plan, and does the team already know?

The data room: evidence, not volume

A technical data room should let a reviewer check your story without needing a meeting for every question. It does not need to be large. It needs to be current, consistent and honest.

Technical data room checklist

Architecture overview: one diagram and two pages of prose, kept up to date.
System inventory: services, data stores, environments and the third parties each depends on.
Delivery process: how code is reviewed, tested and released, with recent evidence.
Security: the policies you actually follow, access reviews, the latest penetration test and what you did about it.
Data protection: a record of processing, data processing agreements with suppliers, and your retention approach.
Intellectual property: employment and contractor agreements with IP assignment, and an open-source licence report.
Incident log for the past year, with what changed afterwards.
Technical debt register: known weaknesses, their impact and the plan for each.
Team structure, responsibilities and where knowledge is documented.
Hosting and tooling costs, ideally expressed per customer.

Two items do more work than the rest. The technical debt register shows that you know where the weaknesses are, which is exactly the judgment investors are trying to assess. The IP agreements are a frequent source of late surprises: a missing assignment from an early contractor can hold up completion while it is put right.

The technical narrative

The data room is the evidence. The narrative is the argument: a short document or a few slides that a founder or CTO can present and defend. It should answer four things.

Where the technology is today, in plain language: what it does, what it is built on, and why those choices were made.
What is genuinely hard to replicate, whether data, workflow, integrations or know-how, and what is not.
What has to change to deliver the plan in the investment case, with an honest view of effort and risk.
What the team looks like now and what it needs to become.

The narrative must match the data room and the code. Reviewers notice when a deck describes a platform and the repository shows a prototype, or when “AI-powered” turns out to be a single call to a third-party model. Neither is a problem in itself. The mismatch is, because it calls everything else into question.

How to prepare

The cost of preparation depends mostly on time. With a few months, almost everything on the checklist is routine: write the documents, chase the missing agreements, commission a penetration test and fix what it finds, add tests around the critical paths. With a few weeks, the same work competes with the diligence itself and with running the company.

Review yourself first Assess the company against the areas above as an investor would, and be blunt about the result.
Fix the cheap, high-signal items IP assignments, licence obligations, access control, secrets in code, and backups you have actually restored.
Write the debt register and the narrative together So the plan for each weakness appears in both, in the same words.
Rehearse Have someone who did not build the system ask the awkward questions, and make sure more than one person can answer them.

Investor readiness is not about looking finished. It is about being able to show, calmly and with evidence, that you know what you have built, where it is weak and what you will do next. That is what holds up.