Technical Due Diligence Checklist for Investors

Investors assess technical debt during acquisitions by asking whether the platform can support the commercial story. A polished demo is not enough; buyers need evidence from the codebase, infrastructure, deployment process, security posture, AI implementation and team.

• Source code ownership: where the code lives, who owns it, who has access, and whether contractor or founder IP has been assigned correctly.
• Deployment process: how releases are tested, approved, deployed, monitored and rolled back when something goes wrong.
• Technical debt: what slows delivery, creates fragility, increases security exposure or raises the future cost of change.
• Security: authentication, access controls, secrets management, dependency risk, incident history and customer data exposure.
• AI claims: whether AI features are proprietary, defensible, measurable and actually used in production workflows.
• Team concentration risk: whether one engineer, founder or agency holds critical operational knowledge.
• Cloud costs: whether infrastructure spend is proportionate to revenue, usage, margins and the growth plan.
• What documentation exists for architecture, onboarding, incidents and operations?

The output should not be a generic IT report. It should translate engineering evidence into deal language: risk ratings, commercial implications, mitigation actions, questions for management and post-close priorities.

This is especially important for AI, healthcare and venture-backed software companies, where valuation often depends on scalability, data quality, regulatory confidence and rapid product expansion after completion.