Technical Due Diligence Checklist for Startup Investors (2026)

Why generic templates fail

Generic tech DD templates miss what kills deals in 2026: AI claims that are not production-ready, architecture that fails under 2× traffic, and engineering teams with inflated credentials that struggle to ship.

This checklist is what I use when doing independent engineering due diligence for VCs and acquirers ($1,250 fixed one-off, one to two weeks).

Architecture & scalability

• Can the current architecture handle 2× and 10× users without a rewrite?
• Monolith vs. services: was the split intentional or accidental?
• What is the bottleneck: database, queue, third-party API, or frontend?

Code health signals

• Test coverage: meaningful tests or coverage theater?
• Deployment frequency and rollback story
• Dependency risk (unmaintained packages, license issues)
• Incident patterns in the last 90 days

Team depth

• Bus factor on critical systems
• Seniority mix vs. what the pitch deck claims
• Hiring plan realism (can they actually close the roles?)

AI / ML claims (often skipped)

• Production AI vs. demo-ware: evals, fallbacks, cost controls?
• Model routing and token spend: is there unexpected bill growth ahead?
• Data pipelines: where training and inference data comes from.

Security baseline

• Secrets handling, auth model, dependency vulnerabilities
• Compliance gaps that block enterprise sales

Deliverables investors use

A one-page traffic-light summary per area, specific findings with repo evidence, and recommended questions for management.

Related service

Technical Due Diligence for Investors & Acquirers - Technical due diligence is an independent engineering review of a target company's codebase, architecture, team capability, and technical narrative - typically …