We Audited 50 YC Startups' AI Search Visibility

Y Combinator's Summer 2026 batch is still a few weeks from Demo Day, but the companies are already live, funded, and building in public. We ran all 50 SaaS and software companies from the batch through Flozi's AEO audit, the same tool we use to score AI search optimization and answer engine optimization (AEO) for any site: how visible a company is to AI answer engines like ChatGPT, Perplexity, and Gemini, and how likely it is to get cited when someone asks those systems a buying question.

The average score: 34 out of 100.

That's a batch of some of the best-funded, most technically sophisticated early-stage teams in the world, most of them building AI products themselves, and most of them close to invisible to the AI systems their own customers use to find tools like theirs.

It's not an access problem

The instinct is to assume low AI visibility scores come down to technical blockers: robots.txt rules, JavaScript rendering, crawlers getting turned away at the door. That's not what the data shows here.

AI Access, whether crawlers can actually reach and read the site, averaged 6.1 out of 7 across the cohort, or 87%. Nearly every company passes on that front. The drop-off happens further down the pipeline, in the three dimensions that actually determine whether an LLM can extract and cite an answer:

• Schema markup: 22% average. Almost nobody is using structured data to tell AI systems what their product does, who it's for, or how it compares to alternatives.
• Answer readiness: 22% average. Homepages are written for humans skimming a hero section, not for an AI system trying to extract a direct answer to "what does this company do."
• Query alignment: 22% average. When we ran real buyer-style queries against each site's content, most companies simply weren't retrievable for the questions their own prospects are asking, the core mechanic behind generative engine optimization (GEO) and getting cited in AI search results.

Chunk extractability, how easily AI tools can lift clean, self-contained passages from the page, was the one bright spot at 68%. The content that exists is at least well-formed. There just isn't enough of it answering the right questions, and what's there rarely carries the schema that helps an AI system trust it.

The full breakdown

Every company below was scored on the same five dimensions and run through the same set of buyer-intent queries. Companies discussed in more detail further down are linked.

Justinian's domain now redirects to a rebrand, Locke. Its score reflects the stale domain rather than the live company, and it's excluded from the analysis below for that reason.

Why the top of the list looks the way it does

Tsenta leads the batch at 72. It's an AI job application agent, and its site does the thing almost nobody else in the batch does: it states plainly, near the top of the page, what the product is for and who uses it, backed by schema markup and a blog that answers specific questions instead of restating the tagline. That combination is most of what answer engine optimization comes down to in practice.

Context and Pango tie for second at 71. Context sells structured web data for AI agents, which means its own team clearly understands what makes content machine-readable, and it shows: full schema, strong chunk extractability, direct answers to "what does this do" and "who is this for." Pango, an agentic OS for e-commerce logistics, gets there through content depth: enough pages, enough specificity, enough coverage of adjacent use cases that the audit's query-matching step found real overlap with how a buyer would actually search.

Codag and Agentcard round out the top five in the low-to-mid 60s. Both are narrow, technical products (log compression for AI incident response, single-use debit cards for AI agent payments) and both write about that narrowness directly instead of hiding behind generic AI-startup language.

The middle of the pack

Most of the batch lands in the 30s and 40s, which the data says is a content and structure problem, not a fundamental one. Companies in this range typically show reasonable chunk extractability, but very little schema markup and thin answer-shaped content, real and specific products described in language too abstract for an LLM to map to a buyer's actual question. The product is often solid. The site just isn't built to be read by a machine yet.

A structural blind spot worth naming

A cluster of the lowest scores in the batch traces back to something more basic than content quality. Several companies are running marketing sites that render entirely in JavaScript, with no meaningful content in the initial HTML response. In our crawl, some of these homepages returned close to zero bytes of readable text on first load. To an AI crawler that doesn't execute JavaScript, that's an empty page, regardless of what the product actually does.

This is one of the easiest issues to miss internally, because a JavaScript-rendered site looks completely normal to a human visitor. It only becomes visible once you check what an AI crawler sees instead of what a browser renders.

Why this matters so much

We've seen more inquiry into SEO and AEO from our clients in the last year than at any point before. Companies that never thought about search optimization as a priority are now asking to invest real resources into it, and that shift is happening across the board, not just with AI-native startups.

Part of the reason is the bar is still this low. A batch of 50 well-funded, technically sophisticated companies averaging 34/100 means the opportunity to stand out is real and immediate. But that also means the window won't stay open. Authority and retrievability get built over time, through consistency, not through a single well-written post. Unless a piece of content is genuinely unique or deeply useful, one blog isn't going to earn you authority on its own. It's a sustained effort, and it isn't only about content and structure either, it's about how a company shows up across the web as a whole.

Here's the part that makes this urgent rather than optional: having a great product and a well-designed website isn't enough anymore. Search and AI query are, without exaggeration, a company's most important marketing channel, because nothing else converts like it.

When someone searches for what you offer or asks ChatGPT for a recommendation, they're arriving with high purchasing intent. That's true across the web, for nearly every kind of buyer. When a company wants to procure something, the first move is a Google search or a prompt to an AI assistant. If you don't show up there, no other channel makes up for it.

Curious where you'd land? Run your site through the same audit, free, and see your score in minutes: flozi.io/free-aeo-audit