The Independent Guide to Technology Due Diligence

Technology due diligence (TDD) is an independent assessment of a company’s technology — its architecture, code, infrastructure, security, engineering team, and intellectual property — set against what the business plans to do with them.

Audits test compliance against a fixed standard. TDD tests whether the technology will support the business plan, what it will cost to run, and where the risks sit.

When TDD happens

Four situations usually trigger it:

• Fundraising — investors at Series A and beyond routinely require an independent technical assessment before committing capital.
• Acquisition — the buyer needs to know what they are buying, what it will cost to run, and what liabilities sit in the codebase.
• Self-initiated healthcheck — the board or CEO commissions TDD to surface problems before an external party finds them.
• Portfolio monitoring — PE firms run periodic TDD on portfolio companies to track technology health over time.

Who conducts TDD

TDD is carried out by independent firms staffed with former CTOs, engineering leaders, and architects — people who have built and run production systems. The work is as much commercial as technical; the code review is only useful insofar as it is translated into business consequence.

A good provider has no commercial relationship with the target or its vendors, bases findings on evidence rather than testimony, and reports what it finds without flattery.

Technology due diligence answers a commercial question with technical evidence: is this technology worth what we are about to pay for it?

A good engagement produces a short, ranked assessment of technical risks and opportunities, with each finding expressed in commercial terms — what it costs to fix, how long it takes, and whether it affects the investment thesis.

Why TDD matters for deals

In most modern businesses the technology is a material part of what the buyer is acquiring and, often, a material part of the risk. That is true even where the business does not describe itself as a technology company.

TDD directly informs:

• Pricing — technical debt, security exposure, and architectural limits translate into costs that a buyer can reflect in valuation.
• Deal structure — material findings may warrant earnout conditions, escrow provisions, or specific reps and warranties.
• Integration planning — understanding the target’s architecture before completion removes most of the expensive surprises.
• Value creation — identifying opportunities for consolidation, simplification, or acceleration in the post-deal roadmap.

What a good TDD covers

Specifics vary by deal context, but the core areas are consistent:

• Architecture fitness — is the system designed to support the business at its current and projected scale?
• Code quality and technical debt — what is the maintenance burden, and is it growing or shrinking?
• Security posture — what is the actual exposure, as distinct from what the policies claim?
• Infrastructure maturity — is the platform reliable, observable, and recoverable?
• Team capability — can the team double in eighteen months without losing the people who matter, and does the engineering organisation have the shape to absorb that growth?
• IP and licensing — is ownership clean, and are there any open-source or third-party licensing risks?

TDD for growth theses

Most TDD framing is defensive — what is broken, what is risky, what will cost money to fix. For a growth-oriented acquirer the more useful questions concern capacity and leverage: what will the platform do that it does not do today, how quickly, and with what investment?

A growth-focused assessment should cover:

• Scale ceiling — where the next bottleneck sits, at what revenue or user volume it begins to bite, and what the shape of the work is to move it. “Ten times today’s load” is the rough test; the sharper question is which failure mode appears first.
• Engineering throughput under expansion — current velocity is a snapshot. What does it look like after eighteen months of aggressive hiring? Throughput rarely scales linearly with headcount, and the answer depends on architecture, tooling, and the maturity of engineering management.
• Hiring and retention — can the target hire into a competitive market, and will the people who matter stay after the ownership change?
• Platform extensibility — the cost of supporting a new geography, a new vertical, a white-label customer, or a multi-tenant deployment. Growth theses often rest on entry into adjacent markets; TDD can test whether the platform is shaped to support them.
• AI and data posture — whether the data the business holds is structured, clean, and accessible enough to support AI features, and whether the engineering organisation has the skills to ship them.
• Defensibility — the extent to which technology contributes to the competitive moat, via data network effects, integrations, workflow lock-in, or switching cost. Commercial DD asks whether the moat exists; TDD tests whether the technology supports it.

Growth-focused findings are forward-looking and investment-oriented. They describe what needs to happen, not only what has gone wrong.

Red flags that should concern you

Patterns that typically indicate deeper problems:

• Technical debt that displaces new capability on the roadmap — a team that spends more time firefighting than building is a team whose output will not scale with headcount, and the gap widens with growth.
• Opacity from the target — attempts to minimise, obscure, or delay access to technical information are themselves a finding.
• Single points of failure — a lone server, a lone engineer, or a lone undocumented process. Concentration risk in technology is as material as concentration risk in revenue.
• Release processes that require a code freeze, a dedicated rota, and a rehearsal for each deployment — the platform is not ready for the cadence a growth thesis will demand.
• IP gaps — missing assignment agreements, undocumented contractor contributions, or unlicensed open-source components create material post-completion liabilities.

How TDD informs valuation

Findings translate into financial impact. A well-structured report provides:

• Remediation costs — investment required to address identified risks, broken into immediate (pre-completion), short-term (first 100 days), and medium-term (first year).
• Risk scoring — each finding categorised by severity (critical, high, medium, low) and likelihood of impact.
• Benchmarking — how the target’s technology maturity compares with similar companies at the same stage.
• Value creation opportunities — where targeted investment (platform work, key hires, a retired subsystem, a data or AI capability) would compound the growth case.

What the TDD firm will need from you

To produce a useful report the assessor needs the commercial context, not only the technical one:

• The investment thesis in plain language, including the specific commercial claims that rest on the technology.
• The management presentation and any model assumptions that are technology-sensitive — user scale, transaction volume, unit cost, roadmap dependencies.
• Data room access, with guidance on which documents are authoritative and which are draft.
• An introduction to the target’s CTO or technical lead, and an agreed process for interview scheduling.
• Clarity on what the report will be used for — price negotiation, SPA structuring, integration planning, or all three.

Without this the assessor is guessing at what matters, and the output reads like a generic technical audit rather than a bespoke commercial assessment.

How TDD fits with commercial, financial, and legal DD

Technology touches each of the other workstreams. A coordinated approach avoids duplicated effort and closes the gaps that open between them:

• Commercial DD assesses the market and the product’s fit for it; TDD assesses whether the technology will deliver the product as the market grows. The two share language around scalability, performance, and the customer experience.
• Financial DD reviews R&D spend, capitalisation policy, and engineering cost base; TDD adds a view on whether the spend is productive and whether the debt trajectory is sustainable.
• Legal DD reviews contracts, employment, and IP assignment on paper; TDD tests whether the facts on the ground match — whether contractor work has actually been assigned, whether open-source components comply with licence terms, whether data processing is consistent with stated contracts.

In practice the TDD firm should exchange findings with the other workstream leads at least twice during the engagement: early, to flag anything that reshapes scope elsewhere; and before the draft report, to reconcile anything that would otherwise appear twice with different framings.

Scope, cost, and what you receive

Engagement scope should match the deal. A sensible proportionality rule:

• Bolt-ons and smaller deals — a two-to-three week red-flag engagement focused on the material risks and the quickly answerable commercial questions.
• Mid-market deals — a four-week full engagement covering the eight assessment areas in appropriate depth, with findings ranked and costed.
• Platform deals or unusually complex targets — six weeks or longer, with deeper code review, architecture workshops, and specialist streams where relevant (security, privacy, data).

Cost scales with scope and team seniority. Expect ranges, not list prices. A provider unable to explain the cost-to-scope trade-off clearly is unlikely to be the right choice.

The deliverable should include an executive summary that a time-pressed MD can read in ten minutes, a prioritised findings table with severity and indicative remediation cost, detail sections for each assessment area, a red / amber / green view mapped to those areas, and recommendations framed by urgency (pre-completion, first 100 days, first year). A narrative report without prioritised findings, or a findings list without commercial framing, is worth asking questions about.

Choosing a TDD provider

Quality varies widely. When selecting a provider, look for:

• Independence — no commercial relationship with the target or any technology vendor.
• Practitioner-led — assessments conducted by people who have built and run production systems, not junior analysts working through checklists.
• Commercial awareness — findings expressed in business terms, not purely technical language.
• Proportionality — scope and depth matched to deal size and risk profile.
• Candour — uniformly positive findings should be treated with suspicion.