What Is Technical Due Diligence?
A practical guide for investors and software founders
Technical due diligence is an independent review of a software company's technology posture before or during an investment or M&A process. For software deals it looks at how the product is built and run, how the team delivers, and whether the technology can support the investment case, not at factory equipment or a pure IT asset inventory.
Venture capital and private equity investors use it to understand material risks and value-creation potential. Software founders use it to prepare early, so avoidable gaps do not surprise them in a raise or a sale. I am an independent consultant based in Berlin, working with investors and software companies across Europe.
This page is the map: a plain-language definition, when the work matters, what a software-deal review usually covers, a practical checklist, and links into the Tech Due Diligence Playbook for deeper notes. For how diligence should serve the deal rather than a checkbox, see Edition 1.
What technical due diligence is
In a software investment or acquisition, technical due diligence is a structured look at the company's technology posture by someone who is not selling the next implementation project. Typical domains include architecture and product platform; engineering execution and quality; security, privacy and compliance; infrastructure, reliability and operations; data, analytics and AI; team, leadership and delivery model; and technical governance and financial awareness.
It is not legal advice, financial modelling, penetration testing alone, ISO certification, or a full line-by-line code audit. Those activities can feed the review. They do not replace a decision-oriented diligence that ranks findings by business impact.
For purpose and risk-register framing, read Edition 1: Deal-Maker, Not Checkbox.
When investors and founders use it
- Before a term sheet, when technology risk should inform price or structure.
- During confirmatory diligence, alongside financial and legal work.
- After close, to turn findings into an owned plan rather than a forgotten PDF.
Depth should match the transaction. A minority stake, a majority buyout, and a carve-out need different scopes. That is the subject of Edition 2: One Size Never Fits All.
Founders who prepare early reduce avoidable friction in fundraising or M&A. See Investment Readiness for Software Startups.
What a software-deal review usually covers
The same seven domains appear across well-run software diligence. Below is a short "what to look for" note for each, with one Playbook deep link. Vendor risk, APIs, resilience, and the post-close plan also matter; they appear in Further reading.
Architecture and product platform
Can the platform support the growth in the investment case, and where do coupling or debt create concentrated risk?
Engineering execution and quality
Do deployment, change-failure, and test signals suggest the team can ship safely at the pace the thesis assumes?
Security, privacy and compliance
Are security claims backed by evidence, and is the regulation path (including GDPR and the EU AI Act where relevant) understood?
Infrastructure, reliability and operations
Are environments, resilience, observability, and cloud cost signals coherent with a company that can scale without surprise outages or runaway spend?
Data, analytics and AI
Are data ownership and foundations clear, and are AI or analytics claims evidenced rather than only marketed?
Team, leadership and delivery model
Where is key-person risk concentrated, and is succession depth realistic for critical roles?
Technical governance and financial awareness
Are tech decision rights clear, and is cost visibility strong enough for the thesis and for post-close oversight?
Technical due diligence checklist for software deals
Use this technical due diligence checklist as a starting map for investors and founders. It is not a substitute for scoped diligence, and it does not claim to be complete or certified.
Scope and deal context
- Deal type and ticket size agreed (minority, majority, carve-out, and similar)
- Investment thesis and tech-dependent assumptions written down
- Depth and timeline agreed with all parties
- Access list: people, repos, cloud, tickets, docs
Architecture and product platform
- Platform can support the growth in the investment case
- Major coupling and modularity risks identified
- Known technical debt classified by business impact
- Product-tech fit checked at a high level
Engineering execution and quality
- Deployment frequency and change failure signals reviewed
- Test and release discipline understood
- Critical path delivery risks noted
Security, privacy and compliance
- Access control and secret handling reviewed
- Evidence behind security claims requested
- Relevant regulation path noted (for example GDPR, EU AI Act where applicable)
Infrastructure, reliability and operations
- Cloud setup and environments mapped
- Resilience and incident history reviewed
- Observability baseline checked
- Cost and FinOps signals sampled
Data, analytics and AI
- Data foundations and ownership clear
- AI and ML claims evidenced, not only marketed
- Data residency and sovereignty constraints noted if relevant
Team and delivery model
- Leadership and key-person risk mapped
- Succession depth for critical roles considered
- Delivery model (in-house and vendor mix) understood
Governance, vendors and money
- Decision rights for tech documented
- Material vendors and lock-in reviewed
- Build vs buy posture understood
- Tech cost visibility adequate for the thesis
Output and next steps
- Material findings ranked by business impact
- Recommendations with owners and timing
- Post-close or pre-close actions separated
- Findings discussed with the investor and, where appropriate, the company
Reminder: a checklist is not an engagement. For purpose and framing see Edition 1. For turning findings into an owned plan see Edition 27.
How deep should the review go?
Right-size by ticket size, company stage, regulation, and deal type. A light directional view can be enough for some minority investments. Larger or more complex transactions usually need deeper evidence.
Edition 2 covers scoping by transaction type. How engagements are scoped in practice is described on Technical Due Diligence for Investors.
Common failure modes
- Treating technical due diligence as a checkbox rather than a decision tool (Edition 1).
- Using one-size scope for every deal type (Edition 2).
- Ignoring cloud cost and FinOps signals (Edition 5).
- Confusing synthetic load tests with realistic capacity proof (Edition 25).
- Skipping people and succession risk (Edition 11, Edition 26).
- Leaving findings without owners or a post-close plan (Edition 27).
Further reading from the Playbook
The Playbook is ongoing operator detail. This page is the overview. Start with these editions, then browse the full index.
- Edition 1: Deal-Maker, Not Checkbox
The purpose of Technical Due Diligence and using a risk register as a deal-making tool
- Edition 2: One Size Never Fits All
Right-sizing Technical Due Diligence scope by transaction type: minority stake, majority buyout, and carve-out
- Edition 3: The Metrics That Matter
Key deployment, incident, and cost signals that predict platform scalability
- Edition 4: Debt or Deal-Breaker?
Technical debt identification, classification, and its impact on deal valuation
- Edition 5: Scaling Without Bleeding Cash
Cloud cost analysis, FinOps practices, and spend optimisation as due diligence signals
- Edition 8: Security & Compliance in the AI Act Era
Security posture and compliance readiness under the EU AI Act and related regulation
- Edition 11: The People Lens
Engineering team quality, leadership capacity, culture, and key-person risk in Technical Due Diligence
- Edition 15: Platform Architecture Assessment
Platform architecture review: modularity, coupling, extensibility, and scalability
- Edition 22: Tech Governance for Hypergrowth
Technology governance frameworks for rapidly scaling organisations
- Edition 27: The Post-Close 100-Day Tech-Value Plan
Turning diligence findings into a sequenced, owned 100-day plan that reduces priced-in risk and builds the value thesis
Frequently Asked Questions
What is technical due diligence in a software deal?
- It is an independent review of a software company's technology posture before or during an investment or M&A process. The aim is to surface material risks and value-creation potential so investors and founders can make clearer decisions.
How is it different from a code audit or a pen test?
- A code audit focuses on source quality. A penetration test focuses on security exploits. Technical due diligence for software deals is broader: architecture, engineering execution, security and compliance, infrastructure, data and AI, team and delivery, and technical governance. Code review and security testing can be inputs; they are not the whole review.
Who usually commissions it?
- Venture capital and private equity investors commonly commission it on the buy side. Software founders also prepare early on the sell side, so they close avoidable gaps before a formal process starts.
What does a good checklist include?
- Deal context and access, the seven technology domains above, vendor and cost visibility, and a clear output: ranked findings, owners, timing, and a separation of pre-close versus post-close actions. A checklist is a starting map, not a substitute for scoped diligence.
Where can I read deeper notes?
- The Tech Due Diligence Playbook on this site goes deeper by topic: purpose and risk registers, scoping by deal type, metrics, debt, cloud cost, security, people risk, and post-close plans.
How do I talk to someone about a live deal?
- Investors can start on the For Investors page. Founders preparing for a raise or sale can start on For Startups. You can also book a short call to discuss scope and fit.
Need this for a live deal?
Investors: see For Investors. Founders preparing: see For Startups. Or book a short call to discuss scope and fit.
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