Technical Due Diligence: A Guide for Software and IT Deals

When an acquirer or investor writes a check for a software business, they are not really buying the marketing site or the slide deck. They are buying the codebase, the architecture, the team that maintains it, and the operational machinery that keeps it running. Technical due diligence is the process of opening that hood and checking whether the engine matches the brochure. I have sat on both sides of these reviews, as a founder handing over access and as an operator helping a buyer poke holes, and the deals that go smoothly are almost always the ones where the technical story was organized before anyone asked.

This guide covers what technical due diligence actually examines, who runs it and when, a practical step-by-step process, a checklist you can lift directly, the red flags that make reviewers nervous, and how a well-structured data room takes most of the friction out of it.

What is technical due diligence?

Technical due diligence (often shortened to tech DD) is a structured assessment of a target company's technology, engineering practices, and technical organization. It sits alongside the other workstreams in a deal: it is one type of review within the broader due diligence effort that also covers financial, legal, and commercial questions.

Where financial due diligence asks "are the numbers real and sustainable?", technical due diligence asks "is the product real, maintainable, and able to scale into the thesis we are paying for?" The scope usually includes:

• Architecture and codebase: how the system is designed, the state of the code, and how much technical debt is hiding under the hood.
• Scalability and performance: whether the platform can handle growth in users, data, and transactions without a rewrite.
• Security and compliance: vulnerabilities, data handling, and whether the company meets the standards its customers expect.
• Infrastructure and DevOps: hosting, deployment, monitoring, and how reliably the thing actually stays up.
• Team and process: who knows what, how decisions get made, and what happens if a key engineer leaves.
• IP and third-party dependencies: who owns the code, and what open-source or licensed components it relies on.

The goal is not to find a perfect codebase, because that does not exist. The goal is to understand the risks well enough to price them, plan for them, or walk away.

Who runs it, and when?

Technical due diligence is typically commissioned by the buy-side: a strategic acquirer, a private equity firm, or a venture or growth investor. The actual review is often run by one of three groups:

• An internal engineering or CTO-led team at the acquiring company, when they have the bandwidth and the domain knowledge.
• A specialist technical DD advisory firm, brought in for independence and pattern-matching across many deals.
• Independent contractors or fractional CTOs, common for smaller deals where a full firm is overkill.

On timing, tech DD usually kicks off after a letter of intent or term sheet is signed, once both sides have agreed on rough deal terms and are willing to invest real effort. In a typical M&A due diligence process it runs in parallel with the financial and legal streams, often over two to six weeks depending on the size and complexity of the codebase. For venture rounds it tends to be lighter and faster, sometimes just a few calls and a code sampling exercise. For a control acquisition of a mature software company, it can be a deep, multi-week engagement with code scanning, architecture interviews, and a full security review.

As a founder, the honest move is to treat it as inevitable and prepare early. The first time someone asks for your architecture diagram should not be the day after the LOI is signed.

The technical due diligence process, step by step

Every reviewer has their own style, but most engagements follow a recognizable arc.

1. Scope and kickoff. The buyer and their advisors define what matters most given the thesis. A deal premised on rapid scaling will weight infrastructure and architecture heavily; a deal about acquiring a team will weight people and process. This is where the information request list gets built.

2. Document collection. The target populates a data room with architecture docs, security policies, dependency lists, and engineering metrics. This is the stage that makes or breaks the timeline, and it is where a good virtual data room due diligence setup earns its keep.

3. Code and architecture review. Reviewers examine the codebase, sometimes through automated scanning tools and sometimes through guided walkthroughs with the engineering team. They look at structure, quality, test coverage, and the realism of the documented architecture.

4. Interviews. This is where the real signal lives. Conversations with the CTO and lead engineers surface what no document captures: the parts of the system everyone is afraid to touch, the contractor who wrote a critical service and left, the migration that has been "almost done" for a year.

5. Security and compliance assessment. Vulnerability scanning, a review of data handling, and a check against whatever standards the customer base demands (SOC 2, ISO 27001, HIPAA, GDPR practices, and so on).

6. Findings and report. The reviewer synthesizes everything into a risk-rated report, usually with a remediation cost estimate and a clear separation between deal-breakers, price-adjusters, and post-close fix-it items.

7. Negotiation and integration planning. Findings feed back into price, reps and warranties, escrow, and the first hundred days of integration planning.

Technical due diligence checklist

Here is a checklist I keep handy. It maps to the questions reviewers actually ask, organized by area. Treat it as the spine of your data room.

Area	What reviewers want	Why it matters
Architecture	System diagrams, data flow, key design decisions	Confirms the product matches the pitch and can scale
Code quality	Repo access, test coverage, linting and CI setup	Signals maintainability and hidden technical debt
Tech stack	Languages, frameworks, and versions in use	Flags obsolete or hard-to-hire-for technologies
Scalability	Load testing results, current vs. peak capacity	Validates the growth thesis
Security	Pen test reports, vulnerability scans, incident history	Surfaces breach risk and remediation cost
Compliance	SOC 2, ISO, HIPAA, GDPR status and evidence	Determines whether enterprise customers stay
Infrastructure	Hosting, IaC, monitoring, backup and recovery	Measures operational maturity and uptime risk
DevOps	Deployment frequency, rollback process, on-call setup	Shows release maturity and team discipline
Dependencies	Open-source inventory and license types	Catches license and supply-chain exposure
IP ownership	Contributor agreements, contractor IP assignments	Confirms the company actually owns its code
Team	Org chart, key-person concentration, documentation	Assesses bus factor and knowledge risk
Roadmap	Product roadmap and known technical debt backlog	Reveals what is promised vs. what is built

If you want a deeper, deal-ready version of this kind of list, the due diligence data room checklist covers the document set across every workstream, not just the technical one.

Common red flags

After enough reviews, certain warning signs start to repeat. None of these is automatically fatal, but each one changes the conversation.

• Key-person concentration. One engineer who understands the entire payments flow and has no backup. If that person leaves, so does the institutional knowledge.
• No tests, no CI. A codebase with little automated testing and manual deploys tells you releases are slow and risky, and that refactoring will be painful.
• Undocumented architecture. When the only architecture diagram lives in someone's head, integration planning becomes guesswork.
• Murky IP ownership. Code written by contractors without proper assignment agreements, or heavy reliance on copyleft open-source licenses that could force code disclosure.
• Security debt. Old, unpatched dependencies, secrets committed to the repo, no incident response history, and no real ownership of security.
• Scalability claims with no evidence. A pitch about handling ten times the load with no load testing or capacity data to back it up.
• A roadmap that contradicts the code. Features described as shipping that turn out to be prototypes, or a "platform" that is really three loosely connected scripts.

The founders who handle these best are the ones who name the problems first. If you know the payments service is fragile, say so and show the plan. Reviewers trust a team that volunteers its weaknesses far more than one that gets caught hiding them.

How a data room streamlines technical due diligence

Almost everything above runs through documents, and the speed of a technical review is mostly a function of how fast reviewers can find what they need. This is where a virtual data room stops being a nice-to-have.

A good data room does a few specific things for tech DD. It centralizes the architecture docs, security policies, dependency inventories, and engineering metrics in one organized place, so reviewers stop emailing you for "the latest version" of anything. It controls access at a granular level, which matters when you are sharing sensitive material like security reports or partial code excerpts and you do not want everything visible to everyone. And it gives you an audit trail: you can see who looked at what and for how long, which is genuinely useful intelligence about where a buyer's concerns actually sit.

The room I set up for our own raise lived in Plox. What I valued most was being able to grant a reviewer access to the technical folder without exposing the financial section, set documents to view-only so nothing walked out the door, and watch the activity log to see which red flags they were circling. When a buyer spends twenty minutes on your incident history, that is a conversation you want to have proactively at the next call.

If you are weighing options, our breakdown of the best data room for due diligence compares what to look for, and the guide to virtual data room cost lays out the pricing models honestly so you are not surprised at checkout. Most providers charge either per user, per page, or on a flat workspace basis, and the right structure depends on how many reviewers you expect and how long the deal will run. Plox uses a flat workspace model with unlimited documents and viewers, which I find easier to reason about during a long diligence cycle than per-page metering.

The point is not the specific tool. It is that organized, access-controlled, trackable document sharing turns the most friction-heavy part of technical due diligence into something close to self-service. The faster reviewers can answer their own questions, the faster you get to a yes.

Frequently asked questions

How long does technical due diligence take?

It depends on deal size and complexity. A light venture-stage review can wrap in a few days of calls and code sampling. A full technical review for a mature software acquisition typically runs two to six weeks, sometimes longer if the codebase is large or the security review is deep. The single biggest variable you control is how quickly you can produce documents, which is why preparing the data room early matters so much.

What is the difference between technical and financial due diligence?

They answer different questions about the same business. Financial due diligence validates the numbers: revenue quality, margins, cash flow, and the sustainability of the financial model. Technical due diligence validates the product and the engineering organization: architecture, code quality, security, scalability, and team. Both feed into valuation, and in a software deal the technical findings can move price just as much as the financials. They usually run in parallel during the same window.

Who pays for technical due diligence?

The buy-side typically commissions and pays for it, since it is part of how they protect their investment. The target company's cost is mostly time and disruption: engineers pulled into interviews, leadership assembling documents, and the focus it takes to keep the process moving. A prepared data room dramatically reduces that burden on the seller's team.

Can technical due diligence kill a deal?

Yes, though it more often reshapes a deal than ends it. Severe findings (unclear IP ownership, a major undisclosed breach, an architecture that cannot support the thesis) can be genuine deal-breakers. More commonly, findings translate into a lower price, escrow holdbacks, specific reps and warranties, or a remediation plan baked into the first hundred days after close. The deals that die outright usually do so because something material was hidden and then discovered.

How do I prepare for technical due diligence as a founder?

Start before you have a buyer. Keep your architecture documented, your dependency and license inventory current, your contractor IP assignments signed, and your security posture honest. Run through a checklist like the one above and fix the cheap, embarrassing stuff (committed secrets, missing tests, stale dependencies) on your own schedule rather than under deal pressure. Then organize everything into a clean data room so that when the request list arrives, you are populating folders rather than scrambling.

Is technical due diligence only for acquisitions?

No. It is most associated with M&A, but investors run a version of it before funding rounds, and it overlaps with other review types. A control deal will pair it with commercial due diligence to test the market thesis, and regulated or cross-border deals may layer in additional checks. The technical workstream is one piece of a larger picture, but for a software business it is often the piece that determines whether the rest of the thesis holds up.