AI-Built Software Technical Due Diligence
Technical due diligence for AI-built software assets
Engage when
- PE/VC evaluating AI-built acquisition target
- Target claims AI-built speed advantage — buyer needs validation
- Corporate development evaluating AI-built target
- Venture studio assessing portfolio company engineering quality
The engagement
A PE/VC-facing technical due diligence engagement for acquisition targets whose product was built with AI coding tools. The engagement answers one question for the investment committee: is this a real software asset, or an impressive AI-generated demo?
The review is conducted through AI-assisted codebase analysis using purpose-built skills — the same methodology as the Vibe-Coded Software Review, adapted for the PE deal process. Output format is IC-ready: fragility matrix, rebuild/refactor cost estimate with engineering-month breakdown and confidence bands, and investment risk summary calibrated for deal decision-making.
Process
Data room & codebase access
Week 1
Technical assessment
Week 2-3
IC deliverable
Week 3-4
Data room & codebase access
Week 1
Technical assessment
Week 2-3
IC deliverable
Week 3-4
Deliverables
- Technical Asset Quality Review
Code quality, structure, maintainability, key-person risk, hidden complexity from AI-assisted authorship. AI-generated code patterns identified and flagged.
- Architecture Risk Assessment
Production architecture vs prototype patterns, integration design, scalability ceiling, supply-chain/dependency exposure.
- Security & Maintainability Review
AI-generated code patterns associated with elevated security risk. Flags where specialist penetration testing is warranted.
- Scalability Assessment
Whether the system can handle the target's stated growth trajectory. Load analysis against claimed metrics.
- Technical Debt Estimate
Quantified, with rebuild vs refactor vs harden cost ranges and confidence bands.
- Rebuild / Refactor Cost Estimate
IC-defensible, with engineering-month breakdown and confidence bands. The artifact for price negotiation and post-close fix budgeting.
- Key-Person Risk Assessment
Who actually understands what was generated. What happens at founder departure. Prompt-dependency analysis.
- Investment / Acquisition Risk Summary
Fragility matrix with deal-impact recommendations: price chip, hold to deal terms, kill, or proceed with conditions.
- Executive / IC Readout
Format matched to IC paper or investment committee presentation.
Who This Is For
Typical Buyers
PE operating partner, deal team lead, VC partner, corporate development, venture studio managing partner
Industries
AI-native targets across SaaS, fintech, insurtech, devtools, B2B vertical software
Why Sparkling Neuronics
- We evaluate AI-built assets like the post-close owner who must live with them — grounded in years of operating around production systems in regulated financial services, not checking a diligence template from outside
- We have participated in PE technical due diligence — we know the artifact format and IC audience expectations
- We build custom review tooling and work hands-on across the AI coding tool ecosystem — we identify AI-generated code patterns that standard TDD vendors miss
Related Services
Explore complementary services that build on this engagement.
Vibe-Coded Software Review
Architect-led production-readiness review for AI-built software
Fix, Refactor or Rewrite Decision Sprint
Defensible path-forward decision for AI-built software
AI-Built Software Production Blueprint
Target production architecture for AI-built software
Ready to discuss AI-Built Software Technical Due Diligence?
No commitment. Confidential. A direct conversation to understand your situation and explore how we can help.