AI startup technical due diligence helps investors determine whether AI creates a genuine business advantage, not just whether a company uses AI. KPMG reports that 78% of dealmakers say AI is changing their M&A assessment criteria, while PwC describes a shift from investment thesis to revenue test.
Tech due diligence for AI companies examines model performance, proprietary data and IP, third-party model dependencies, production readiness, security, and unit economics. The goal is to distinguish durable technical assets from rented capabilities and validate claims with evidence rather than demos.
Data provenance and ownership matter. Unclear rights or improperly sourced training data can create legal exposure and, in serious cases, leave a model or other technology asset unusable.
Technical findings should inform investment decisions. A rigorous review helps investors assess valuation assumptions, identify remediation costs, negotiate deal protections, and prioritise post-investment improvements.
The key question is whether the technology supports the valuation. Dextra Labs helps investors, VC and PE firms, and acquirers evaluate AI-related technical risks before committing capital.
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