Technical due diligence purpose-built for investments in AI
We de-risk investments in AI for PE, VC, and M&A by determining whether AI systems can scale reliably, sustain margins, and remain defensible in real-world deployment
AI companies often fit strong investment theses, yet struggle post-investment. Many pivot repeatedly or turn into repair funds. Why didn’t conventional due diligence help?
Conventional technical due diligence was built for deterministic SaaS systems. It verifies that the software works. It does not examine whether an AI system can survive real-world scale.
Most reviews are led by generalist teams and structured around checklists. They confirm surface functionality — not scaling behavior, unit economics, or structural defensibility.
AI systems operate under different constraints. Performance depends on data quality, model limits, and inference cost structure. Complexity and cost do not scale linearly. Structural weaknesses surface as margin compression and fragile defensibility.
Superficial review is insufficient. AI investments require practitioner-led investigation to expose performance limits, scaling fragility, margin erosion risk, and defensibility gaps before capital is deployed.
The ImpactMode advantage
ImpactMode delivers technical due diligence designed specifically for AI investments.
Our work is led by applied AI practitioners who investigate AI systems at the level where risk resides — data integrity, model constraints, scalability limits, inference economics, and structural defensibility.
We work directly with PE, VC, and M&A deal teams to determine whether an AI system is technically viable, economically sustainable, and defensible at scale — before capital is committed.
Our operating principles
Independence over alignment.
Technical realism over aspiration.
Evidence over narrative.
Clear conclusions over ambiguity.
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