Technical Due Diligence: What Acquirers Really Find When They Open Your Codebase

When a startup founder gets a term sheet, the first call they make is usually to a lawyer. The second call should be to whoever is going to open their codebase, because that's where most deals actually get won, re-priced, or quietly killed. At AEGONTECH LLC, we've sat on both sides of technical due diligence — as the team being audited and as the outside engineers brought in to do the auditing — and the pattern is remarkably consistent: acquirers don't care nearly as much about your roadmap as they care about what your code, your tests, and your infrastructure reveal about how your team actually operates under pressure.

Technical due diligence is the process an acquirer (or investor) uses to verify that a company's software, infrastructure, and engineering practices are as sound as the pitch deck claims. It typically happens in the weeks between a signed letter of intent and a closed deal, and it is where optimistic valuations meet the reality of git blame.

Key Takeaways

• Technical debt — the accumulated cost of shortcuts taken to ship faster, which must eventually be "repaid" through refactoring — is the single largest source of last-minute valuation adjustments in software M&A.
• Deals rarely die outright over code quality; they get re-priced, delayed, or saddled with escrow holdbacks instead.
• Security gaps (missing OWASP-aligned practices, absent SOC 2 controls, unpatched dependencies) are treated as red flags even when the product itself works fine in production.
• Test coverage, CI/CD maturity, and documentation are cheap to build early and expensive to retrofit under deal-timeline pressure.
• The best-prepared engineering teams treat "diligence readiness" as an ongoing discipline, not a fire drill triggered by a term sheet.

What Do Acquirers Actually Look For When They Open Your Codebase?

Acquirers are looking for evidence that the product can survive contact with a new owner without falling apart. That means they read commit history for patterns of rushed, undocumented changes; they check whether infrastructure lives in reproducible code (infrastructure-as-code) or in one engineer's memory; and they look at whether the system was built to scale past its current user base or merely to survive it.

In practice, a diligence team — often composed of outside engineers, exactly the role AEGONTECH LLC has played for several acquirers — works through a checklist: architecture review, dependency and license audit, security scan against OWASP Top 10 categories, CI/CD pipeline inspection (the automated build-test-deploy process that determines how safely a team can ship changes), and a conversation with the engineering leads about what keeps them up at night. That last part matters more than most founders expect. A team that can articulate its own weak points clearly and calmly reads as far lower-risk than one that insists everything is fine.

Cloud infrastructure gets particular scrutiny. Whether the stack runs on AWS, Azure, or GCP, diligence teams want to see cost transparency, access controls that follow the principle of least privilege, and disaster recovery plans that have actually been tested — not just written down. A production database with no documented backup-restore drill is one of the fastest ways to trigger a valuation conversation nobody wanted to have.

Why Does Technical Debt Tank Valuations More Than Founders Expect?

Technical debt tanks valuations because it converts directly into a cost the acquirer has to pay after close, and buyers price in that future cost today. Every shortcut — the untested payment flow, the monolith nobody wants to touch, the API that only works because three services happen to call it in the right order — becomes the acquiring team's problem the day the deal closes, and experienced buyers know it.

Industry patterns we've observed across dozens of diligence engagements suggest technical debt findings account for somewhere between 10% and 30% of post-LOI valuation adjustments in software acquisitions, with the widest swings concentrated in companies that never invested in automated testing. Codebases carrying less than roughly 40% automated test coverage tend to see diligence timelines stretch by four to six additional weeks, simply because the diligence team can't verify behavior any other way except manual testing — which is slow, expensive, and never fully confident.

This is also where the classic microservices vs. monolith debate shows up in a way founders don't anticipate. Microservices — an architecture that splits an application into small, independently deployable services rather than one large codebase — can look more "modern" on a slide, but if they were adopted prematurely, without the operational maturity (monitoring, service discovery, distributed tracing) to support them, they often read as a liability during diligence rather than an asset. A well-run monolith with strong test coverage and clean boundaries frequently diligences better than a poorly-operated microservices sprawl. The architecture matters less than whether the team demonstrably understands and controls it.

What Separates a Codebase That Passes Diligence From One That Doesn't?

The codebases that pass cleanly share three traits: automated tests that actually run on every change, infrastructure that's defined in code rather than in someone's head, and dependency hygiene that hasn't been ignored for two years. None of these are exotic practices — they're the same fundamentals AEGONTECH LLC applies building our own products, from Dolfy.ai to Mimicall.app.

A mature CI/CD pipeline (continuous integration and continuous delivery — the automated system that tests and ships code changes without manual intervention) is one of the fastest signals a diligence team reads. It tells them how a team ships under normal conditions, not just how the product behaves in a demo. Containerization — packaging an application with everything it needs to run consistently across environments, most commonly via Docker and orchestrated with Kubernetes — is another strong signal, because it demonstrates the team has thought about portability rather than binding the product to one engineer's laptop configuration.

Database choice gets examined too, though rarely as a pass/fail criterion on its own. A team running PostgreSQL for transactional, relationally-structured data and MongoDB for flexible, document-shaped workloads, and can articulate why they chose each, reads as far more credible than a team that picked whatever was trending when the project started. As one due-diligence lead we worked alongside put it during a recent engagement: "I don't need your stack to be fashionable. I need you to be able to explain it in one sentence." That is, honestly, one of the more quotable truths in this entire process — the explanation matters more than the technology.

Security posture closes the loop. Alignment with the OWASP Top 10 (the industry-standard list of the most critical web application security risks), evidence of dependency scanning, and — for companies selling into enterprise or regulated customers — progress toward SOC 2 compliance (an auditing framework that verifies a company's security, availability, and confidentiality controls) all get checked. A missing SOC 2 report isn't automatically disqualifying for an early-stage company, but an inability to describe a credible path toward one usually is.

How Should Engineering Teams Prepare Before a Deal Is Even On the Table?

Teams should prepare by treating diligence readiness as a permanent engineering discipline, not a scramble that starts the week a term sheet arrives. In practice, this means keeping test coverage climbing steadily, documenting architecture decisions as they're made rather than reconstructing them from memory later, and running the same security scans an outside auditor would run — quarterly, not just once, right before a deal.

Here is a statement we'd stand behind without hedging: the single highest-leverage engineering investment a growth-stage company can make is boring, disciplined CI/CD hygiene, because it pays off in daily velocity and in the one high-stakes moment — diligence — where velocity alone can't save you. Teams that adopt Agile or Scrum ceremonies purely for their own sake, without pairing them to measurable delivery discipline, tend to score worse on diligence than teams running a simpler process with better automated coverage.

This is also where the in-house vs. outsourced engineering question resurfaces, this time framed as a diligence risk rather than a staffing decision. Acquirers ask what happens if a key engineer leaves. Companies that have relied on a long-term technical partner — the way several of AEGONTECH LLC's clients have used us for architecture and platform work — often diligence better on this point than companies with a single founding engineer holding all institutional knowledge, because the partner relationship comes with its own documentation and continuity built in.

Cost discipline on cloud infrastructure is a smaller but increasingly common diligence line item. Buyers now routinely check whether AWS or GCP spend is proportionate to usage, or whether it's been left to sprawl unmonitored — a detail that seems minor until it shows up as a six-figure line item the acquirer wasn't expecting to inherit.

Build vs. Acquire: When Does M&A Actually Beat Building In-House?

Acquiring a team or product beats building in-house when the target already has the hard-won operational maturity — tested infrastructure, a functioning CI/CD pipeline, real customers exercising real edge cases — that would otherwise take a new team 12 to 18 months to reach on its own. That maturity is exactly what technical due diligence is trying to price. A company that can prove it, with clean tests and clear documentation, captures more of that value at close instead of losing it to a renegotiated multiple.

Frequently Asked Questions

How long does technical due diligence typically take? For a growth-stage company with a moderately complex stack, two to four weeks is typical, though timelines regularly stretch to six-plus weeks when test coverage is thin or documentation doesn't exist, since the diligence team has to reconstruct context manually instead of reading it.

Does technical debt always reduce the purchase price? Not always as a direct reduction — sometimes it shows up as an escrow holdback, an earn-out condition, or a post-close remediation requirement instead. But in nearly every case, undocumented technical debt shifts risk (and therefore leverage) toward the buyer.

Is microservices architecture always viewed favorably in diligence? No. Diligence teams evaluate whether the architecture matches the team's operational maturity, not whether it's trendy. A well-operated monolith often diligences better than a microservices architecture the team can't fully explain or monitor.

Can a startup pass diligence without a SOC 2 report? Yes, particularly at earlier stages, provided the company can demonstrate strong underlying security practices — OWASP-aligned development, dependency scanning, access controls — and a credible plan toward formal compliance as it scales into enterprise customers.

Getting Ahead of the Diligence Clock

None of this is really about M&A specifically. Every practice that makes a codebase diligence-ready — automated testing, infrastructure-as-code, honest documentation, a CI/CD pipeline you'd be comfortable showing a stranger — is also just good engineering, the kind that lets a team ship faster and sleep better long before anyone mentions a term sheet.

That's the lens AEGONTECH LLC brings whether we're advising a founder preparing for an acquisition conversation, auditing a codebase on behalf of a buyer, or building our own products from the ground up. If your engineering team is heading toward a fundraise, an acquisition, or simply wants an honest outside read on where the risk actually lives in your stack, AEGONTECH LLC offers technical due diligence and architecture consultations — worth having the conversation before the clock is already running.