Your Series A Pitch Deck Needs an AEO Score

Five years ago, a VC evaluating your startup would Google your company, check Crunchbase, and ask their network. Today they also ask ChatGPT.

"What are the leading developer tools for API testing?" "Who are the main competitors in the AI code review space?" "What do customers say about [your startup]?" These are real queries VCs are running through AI assistants. Not hypothetical. Real.

When the AI answers, it pulls from structured, citation-ready sources. If your startup has proper schema, an llms.txt, and content that matches these queries - you appear in the answer alongside your competitors. If you do not, the investor hears about your competitors and not about you.

This is not about vanity. This is about deal flow. An investor who sees your name in an AI-generated market landscape before your intro email has context. They know what you do. They know where you fit. The conversation starts at a higher level.

Here is an observation from analyzing startup scores across 12 YC batches. The startups with the highest AEO scores tend to be the same ones with strong technical execution across the board. It is not a coincidence.

AEO score is a proxy for several things investors care about: - Technical sophistication: Founders who set up llms.txt and schema on day one understand modern infrastructure - Market awareness: Knowing that AI visibility matters signals awareness of how distribution is evolving - Attention to detail: Proper metadata, clean HTML, structured data - these reflect engineering discipline - Growth orientation: Startups optimizing for AI discovery are thinking about distribution channels their competitors have not considered

We are not saying AEO score predicts fundraising success. We are saying it correlates with the kind of technical rigor investors look for. And when two startups in the same space pitch the same fund - the one that appears in AI answers has a demonstrable advantage.

You do not need a full slide dedicated to AEO. But there are three places where AI visibility data strengthens a pitch:

1. Market slide - competitive positioning Instead of a generic 2x2 matrix, include a real data point: "We score 67/100 on AI readiness. Our top 3 competitors average 34. When prospects ask ChatGPT about our category, we appear in the answer and they do not."

That is specific. Quantified. Verifiable. Investors can check it.

2. Distribution slide - acquisition channels "AI-assisted discovery is our fastest-growing acquisition channel. We appear in ChatGPT and Perplexity answers for 12 of 15 tracked queries in our category." This is a distribution insight most startups cannot articulate because they have not measured it.

3. Technical depth - infrastructure maturity "We ship with AEO infrastructure from day one: llms.txt, full schema coverage, AI-optimized FAQ, semantic HTML." This signals technical maturity in 10 seconds.

The bar is low. 98% of startups cannot show any AI visibility metric. Having one makes you memorable.

Every YC batch has a leaderboard on our platform. Top startups by AEO score, with links to full audit reports and visibility analysis.

What this means for investors: instant context. "This startup ranks #3 in their batch for AI readiness" tells a story. It says the founders understand distribution. It says they are building infrastructure, not just features. It says they are visible where their customers are looking.

What this means for you: differentiation. When an investor reviews 30 startups from your batch, the ones with audit reports and leaderboard positions stand out. Not because AEO is the most important thing about your startup - it is not. But because it demonstrates a dimension of competence most startups have not considered.

The leaderboard is free. Your audit is free. The data is public. Use it.