A technical due diligence checklist is a structured framework used to audit a target company's codebase, infrastructure, and engineering processes to quantify inherited risk. While often viewed as a static list of requirements, in practice, it serves as a diagnostic tool to determine if the technical reality of a product supports the financial assumptions of a deal.
The gap between a "clean" codebase and a scalable business is often where the most significant valuation risks reside. Many acquirers mistake a code audit for due diligence; however, a code audit only tells you if the software is well-written, whereas due diligence tells you if the software is a liability. The primary objective is to move from subjective claims (such as "the system is scalable") to verified evidence.
Provenance and AI-Generated Code
The emergence of LLM-assisted development has shifted the weight of the checklist. In previous cycles, code provenance was a secondary concern. Now, it is a primary risk indicator. As noted by DevEntia, a meaningful share of modern codebases is written by founders or contractors using AI tools, often resulting in modules that no one on the current team fully understands.
The risk is not the use of AI itself, but the lack of human oversight. AI can produce confident, well-formatted code that passes a superficial skim but fails under adversarial input or creates "hallucinated" dependencies. When reviewing a checklist, the focus must move toward the "paths that matter" (authentication, payments, and data ingestion) where a plausible-looking but flawed AI-generated function can lead to critical failures.
Architecture and Scalability Thresholds
Architecture must be evaluated against the projected growth targets of the acquisition. If the business plan assumes a ten-fold increase in users, a monolithic architecture that is currently stable may become a critical bottleneck within six months. Evaluation should be anchored in specific scalability axes.
| Attribute | Acceptable (Low Risk) | Warning (Medium Risk) | Critical (High Risk) |
|---|---|---|---|
| State Management | Stateless services; external cache | Session state in memory | Session state tied to specific servers |
| Database Load | Read/Write separation (Master/Slave) | Single instance with vertical scaling | No indexing on core query paths |
| Deployment | Fully automated CI/CD pipeline | Manual triggers; documented steps | Deploys depend on a single laptop |
| Fault Isolation | Asynchronous calls across services | Synchronous calls with timeouts | Cascading failures; no circuit breakers |
| Environment | Infrastructure as Code (Terraform/Bicep) | Mixed manual and scripted | Hand-configured servers; no registry |
The presence of "microservices" as a label is often a red flag if the reality is a "distributed monolith": multiple services that must be deployed together and share a single database. This increases operational complexity without providing the benefits of independent scaling. This structural misalignment is a key focus when executing Cloud Architecture Due Diligence: What to Look For.
Security and Account Ownership
Security diligence is often reduced to a penetration test, but the most deal-breaking findings are usually administrative. Account ownership is a common point of failure; finding that the AWS root account or the Apple App Store credentials are held in a founder's personal email rather than a corporate entity creates a significant legal and operational risk.
Security must be verified through evidence, not logos. A company may claim SOC 2 compliance, but if the internal access control policy allows every developer root access to production data, the certification is a lagging indicator of a poor security posture.
Effective security diligence focuses on these specific failure modes:
- UI-only authorization: Where tenant data is reachable by simply changing an ID in the URL because the server does not verify ownership.
- Untested backups: Backups that are configured but have never been successfully restored to a clean environment.
- Secret leakage: API keys and database passwords committed directly into the source code repository.
- Unassigned IP: Contractors who contributed core logic but never signed an explicit copyright assignment.
- The "Bus Factor": A system where only one person understands the core logic and that person is not staying post-acquisition.
These risks are explored in depth within Cybersecurity Due Diligence: Where to Start.
Operational Maturity and the SDLC
The health of a technical organisation is revealed in its Software Development Life Cycle (SDLC). A team that deploys large payloads infrequently is at higher risk than one that deploys small changes continuously. The checklist should examine the "Definition of Done" to see if it includes customer adoption and performance metrics or merely the act of merging code.
According to the AKF Partners framework, operational maturity is measured by the ability to find problems before customers do. This requires a transition from basic system-level monitoring (CPU/RAM) to synthetic monitors and business-level metrics (e.g., "successful checkouts per minute").
The following operational markers differentiate a professional engineering org from a "vibe-based" MVP:
- Code Review: Mandatory peer reviews with defined standards.
- Automated Testing: Unit test coverage exceeding 75% on critical paths.
- Incident Management: A centralized log of production issues with documented post-mortems.
- Technical Debt Tracking: A formal process for prioritizing the reduction of tech debt within each sprint.
- Onboarding Velocity: A documented runbook that allows a new engineer to make a meaningful change within their first week.
Intellectual Property and Asset Integrity
A technical checklist must extend beyond the code to the legal rights governing it. It is common to find that core modules were developed by freelancers without a written assignment of rights. This creates a "cloud" over the title of the software, making the asset legally precarious.
As detailed by RingStone, the audit must include a review of open-source license compliance to ensure the target has not incorporated "copyleft" code (such as GPL) in a way that forces the proprietary codebase to become open source. This is a critical risk for any company whose valuation is based on the exclusivity of its IP.
The audit should verify:
- Contributor Agreements: Every person who committed code has a signed agreement assigning ownership to the company.
- License Attribution: A comprehensive list of third-party libraries and their respective licenses.
- Patent Alignment: Verification that the implemented technical solutions match the claims in any filed patents.
- Dependency Provenance: A check for "abandonware" in the manifest, packages that are no longer maintained but are critical to the build.
- Domain and SSL Ownership: Confirmation that all digital identities are held in corporate accounts.
Turning Findings into Valuation
A findings list is not a decision; it is data. The final step of the process is to map technical failures to financial impact. This is where the IT Due Diligence Process: What Good Looks Like becomes essential, as it converts "Major" or "Critical" findings into remediation estimates measured in engineer-weeks.
If a system requires a partial rebuild to support the projected roadmap, the cost of that rebuild should be deducted from the purchase price or held in escrow.
The most dangerous technical debt is not the messy code, but the knowledge gap.
Sources
- Technology Due Diligence Checklist — AKF Partners: covers scalability axes, operational processes, and security policies.
- Technical Due Diligence Checklist 2026 | DevEntia: analyses the impact of AI-generated code and provides a scoring rubric for remediation.
- Technical Due Diligence Checklist & 85 Areas for Tech Due Diligence Questions [2026] | RingStone: provides comprehensive coverage of IP ownership and open-source licensing risks.
