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Get scored on what pre-seed AI investors evaluate — technical differentiation, data moat potential, team ML expertise, and market timing — then match with AI-focused angels.

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Ben Wiggins

Ben Wiggins

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7x Founder, 1 Exit, Experienced Angel Investor, Family Office

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Growth Ceiling Calculator

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Investor Readiness Quiz

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Frequently Asked Questions (FAQ)

Everything you need to know about getting your pitch deck investor-ready

What do pre-seed AI investors want to see?

At pre-seed, AI investors look for: team with genuine ML expertise (papers, experience), a unique data or model advantage (not just GPT wrappers), a clear wedge into a specific market, and evidence of customer pull. You don't need revenue, but you need a credible technical thesis.

How much can I raise for a pre-seed AI startup?

AI pre-seed rounds are running $500K-2M at $8-15M valuations in 2025-2026. The premium exists because compute costs are high and AI talent is expensive. Be specific about use of funds: GPU costs, key hires, and customer acquisition.

How do I differentiate from other AI startups?

Three paths to differentiation: proprietary data (unique training data others can't get), domain expertise (deep knowledge in healthcare, legal, finance), or technical innovation (novel architectures, efficient fine-tuning). "We use LLMs" is not a moat.

Should I build on foundation models or build my own?

At pre-seed, most investors accept building on foundation models (GPT-4, Claude, Llama) if you have a clear path to differentiation through fine-tuning, data, or application-layer innovation. Building from scratch requires a compelling reason and significantly more capital.

What should my first AI product milestone be?

Ship a focused, working product to 10-50 design partners within 3 months of funding. Prioritize a narrow use case where AI performance measurably exceeds alternatives. Early users who can provide feedback loops for model improvement are worth more than broad launches.

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