Where to apply AI in capital workflows

Use case

Pre-seed deck triage in 24 hours

Run deck triage as a confidence-gated diligence system: score each claim, surface missing evidence, and decide go-deeper versus pass in 24 hours.

You need a lens on value capture, not only TAM and growth claims.

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Use case

Enterprise AI pilot readiness check

Ship pilots only when value metrics, risk controls, and owner accountability are explicit; otherwise hold scope and fix prerequisites.

You need pilot scope tied to measurable economic outcomes.

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Use case

AI flywheel and moat design

Use this when your product works today but your long-term advantage story is still weak.

You need outcome data, not just usage logs, to improve model quality.

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Use case

Fundraising narrative pressure test

Rewrite the story as a decision chain: bottleneck, proof, economics, and moat, with explicit evidence for each link.

Your metrics are improving but investor conviction is not.

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Use case

Board-ready risk signal refresh

Use this when updates are frequent but board conversations still feel reactive and unfocused.

You need a single view of technical, GTM, and execution risk movement.

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Use case

GTM experiment prioritization for AI products

Use this when your team has many GTM ideas but no clear sequence tied to durable advantage.

Your ICP assumptions are changing and experiments are overlapping.

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