Due Diligence Checklists › AI & ML › Pre-Seed
AI & ML Startup Investment Checklist: Pre-Seed Stage (2026)
This checklist covers 27 due diligence items for AI & ML startups at the Pre-Seed stage. Each item has been validated against institutional investor practice. DDR automates the majority of these checks from a single pitch deck PDF upload.
27 checklist items · 6 red flags automatically detected · See a sample DDR report
Pre-Seed Requirements
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Founding team quality and relevant domain expertise
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Problem evidence: clear pain, ideally lived experience
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Market size: TAM must justify a venture-scale outcome
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Early signal of demand: waitlist, LOIs, or first customers
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Founder-market fit: why this team for this problem
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Proprietary insight competitors don't have
AI & ML Sector
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Model performance benchmarked against GPT-4 and best public baseline
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GPU cost projection modeled at 10x current usage
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Proprietary data asset documented: source, size, labeling methodology
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Data licensing rights confirmed for all training data
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Research background of technical founders verified
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No trademark or IP conflicts with existing AI companies
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Safety evaluation completed for high-stakes applications
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Customer contracts include data usage rights for model improvement
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Competitive landscape map includes all well-funded AI players in category
Deep Dive
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Verify model performance benchmarks on standardized test sets — request methodology, not just results
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Review GPU infrastructure costs and projection of costs at 10x and 100x scale
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Assess proprietary data strategy: size, collection method, labeling quality, update frequency
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Check for any data licensing issues: training on copyrighted content without clear rights
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Review model safety and hallucination rate for high-stakes use cases
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Evaluate team's AI research background: publications, prior models, GitHub contributions
Regulatory
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Verify: EU AI Act: high-risk AI systems face mandatory conformity assessments and CE marking by 2026
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Verify: US Executive Order on AI safety: compliance requirements for frontier model developers
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Verify: Copyright liability: training on unlicensed data; ongoing litigation in US and EU
OSINT Signals
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Check: GitHub repository activity: commit frequency, star count, contributors
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Check: ArXiv and Google Scholar: published papers citing the company's research
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Check: LinkedIn team composition: ratio of ML engineers/researchers to sales/marketing
DDR AUTOMATES THIS CHECKLIST
Upload an AI & ML startup pitch deck and DDR automatically completes 19+ of these 27 checklist items — sourcing data from 13 OSINT signals, benchmarking against 4 comparable companies, and detecting all 6 critical red flags.
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