Pavel Shpin - Technical Due Diligence ExpertInvest with conviction.
De-risk your dealflow.
Get a founder-level competency audit that translates technical risk into a clear Go/No-Go verdict on execution risk - in 3 Days.
From Geek-Speak to Investment Thesis
Standard TDD audits miss the new AI-era risks that can destroy enterprise value. When employees leak IP through ChatGPT, when AI-generated technical debt creates an unmaintainable codebase, or when your "AI whisperer" quits—these aren't just technical issues. They're material threats to your returns. My reports translate these emerging risks into clear business impact assessments for your investment committee.
Auditing the Team, Not Just the Tech
Early-stage investing is a bet on people. I use a startup's technology as an unforgiving 'mirror' to assess the founding team's discipline, foresight, and resilience—the true predictors of venture-scale returns.
"A brittle architecture suggests a tactical, short-term-focused team. A robust, scalable architecture suggests a strategic, long-term-focused team capable of building enduring value."
Decision-Support Tools, Not Just Findings
The Verdict
A clear Go/Go with Conditions/No-Go recommendation.
The Risk Matrix
A prioritized matrix quantifying every finding by business impact and likelihood.
The IC-Ready Summary
A concise one-page executive summary designed for efficient review.
Recent AI-Era Diligence Examples
Seed B2B SaaS
72-hour TDD; identified key-person CI/CD risk and fragile scaling. Verdict: Go with conditions.
Series A DevTools
Founder-side readiness; AI governance instituted; clarified model risk and roadmap fit.
Healthcare Data
Independent TDD on data lineage and model drift; IC-ready risk-to-impact mapping.
Case Study: The $500M+ AI Failure at Zillow
The spectacular failure of Zillow Offers is a masterclass in AI-era risk. It wasn't just a bad algorithm; it was a catastrophic failure of strategy caused by a trifecta of model drift, flawed KPIs, and a lack of AI observability. My diligence process is explicitly designed to detect these kinds of systemic risks before they can impact your portfolio.
AI-Era Risk Assessment That Traditional Audits Miss
The AI era has created entirely new categories of existential risk. Beyond code quality, I audit for Shadow AI data exposure, algorithmic bias in AI-generated outputs, phantom IP ownership of AI-created code, and "concept drift" in production models. These emerging risks require a founder's perspective to identify—they're invisible to conventional TDD checklists but can obliterate enterprise value overnight.
"Your biggest data breach threat isn't a hacker. It's your employee's ChatGPT window. When proprietary data is pasted into a public LLM, it can be absorbed and become a permanent, irreversible leak of your intellectual property."