AthenaHQ
Be the answer.

Here is a thing that is true and slightly unsettling if your job is marketing: a growing share of your future customers will never see your website before they decide what to buy. They will type a question into ChatGPT or Perplexity or Claude, read a paragraph, and act on it. The paragraph will name some brands. If yours isn't one of them, you will not get a notification. There is no page two. There is the answer, or there is nothing.

AthenaHQ is a company built entirely around that sentence. Founded in 2025 and part of Y Combinator's Winter 2025 batch, it sells software that does something that sounds simple and turns out to be genuinely hard: it tells brands how AI models talk about them, and what to change so the models talk about them more favorably. The category has an unlovely name - Generative Engine Optimization, or GEO, with a cousin called Answer Engine Optimization, or AEO - but the pitch is easy enough. It is SEO, rebuilt for the machine that answers instead of the machine that links.

The tricky part, and the reason this is a business and not a spreadsheet, is that AI search is fundamentally invisible. When you googled something, you and your competitor saw roughly the same ten blue links, and you could go count your position. When someone asks an AI, the answer is generated fresh, privately, slightly differently every time, and shaped by which sources the model happened to cite. Nobody can just "look at their ranking." So AthenaHQ does the looking at scale - it says it continuously analyzes more than three million real-world AI responses and maps them to over three hundred thousand citation sites, then turns that into something a marketing team can actually act on.

That "act on" bit matters, because plenty of tools will hand you a chart showing that ChatGPT ignores you, which is interesting for about four seconds and then just makes you sad. AthenaHQ's stated goal is to end each insight in a to-do: this is the content gap, these are the citation sites that shape the answer, this is the prompt category where your competitor owns the conversation. It bundles monitoring (how am I doing across the models), prompt volume (what are people actually asking), content agents (generate the GEO-ready material), and brand integrity (catch the model when it invents a wrong price or a fake feature about you). There's a Shopify integration for ecommerce catalogs and a workspace for agencies running this on behalf of clients.

The founders are, conveniently, exactly the people you'd want building this. CEO Andrew Yan was a product manager on Google Search's information-acquisition team and worked on DeepMind's generative-media group; he studied math and computer science at Columbia. There is a nice irony in a person who helped build Google Search leaving to instrument its likely successor - though "likely successor" is doing some work, and Yan would be the first to say the old system isn't going anywhere quietly. His co-founder and CTO, Alan Yao, is an ex-ServiceNow platform engineer who was building on OpenAI's tools before ChatGPT was a public thing. The team fills out with alumni of Cohere, Reputation.com, and adjacent worlds - people who have thought professionally about both how models work and how brands manage what the internet says about them.

The money followed the thesis. AthenaHQ launched from stealth with a $2.2 million seed round - reporting elsewhere pegs total funding a bit higher across rounds - backed by Y Combinator, FCVC, Red Bike Capital, Amino Capital, and a roster of angels from DeepMind, OpenAI, Anthropic, and Google, including, per the company, the creator of Google Image Search. That investor list is basically a bet that the people who built the current AI stack think brands will pay to be legible inside it. The customer list is the other half of the argument: AthenaHQ says it works with 200-plus companies, from fast-growing AI startups like Julius and Greptile to publicly traded names like SoFi and Coinbase and consumer brands like Paperless Post. When public companies start tracking their AI-search share of voice, it stops being a growth hack and starts being a line item.

Is any of this durable? Reasonable skeptics point out that the AI platforms could build native analytics, or that "optimizing for the model" is a moving target that resets every time a model updates. Both are fair. But the same objections were leveled at SEO in roughly 2004, and SEO became an industry worth tens of billions of dollars precisely because the target kept moving and someone had to keep watching it. AthenaHQ's whole bet is that AI search is at that same awkward, lucrative stage - too big to ignore, too new to measure - and that being early is the point.