Unusual raises $3.6 million from BoxGroup, Y Combinator, Long Journey Ventures, Instacart founder Max Mullen, Phosphor Capital, and others to help brands understand and change the way that AI models talk about them.

The goal of AI brand alignment is to ensure AI models' view of your brand matches reality. Not to game the models, but to give them accurate, specific information so they can represent you fairly when buyers ask the right questions.

AI brand alignment is the practice of ensuring that AI models talk about your brand in the same way that you talk about your brand.

A number of AEO/GEO tools rely on prompt datasets for "prompt volume." Despite sounding useful, the data is sufficiently broken to render it useless for strategy.

A Chrome extension marketed for privacy and security has been secretly harvesting AI conversations and selling them to data brokers. The extension, Urban VPN Proxy, has over 6 million users and carries Google's "Featured" badge—meaning it passed manual review and met what Google describes as "a high standard of user experience and design."

We ran an experiment over hundreds of thousands of conversations with AI models to determine what kind of content (short form, long form, directories, documentation, etc..) AI models prefer when collecting sources to answer questions. We found that AI models preferred long-form content over more than any other type combined. The implication is that marketers should make information about their business available via long-form content rather than just website pages or landing pages.

Brands rely on comparison content (listicles, X vs Y...) to promote their product. Intelligent AI models can see through thinly-veiled promotional content, which backlashes against the brand. In this article, we describe how to write comparison content that works in the AI age.

Your marketing pages are optimized for conversion. Your blog is optimized for engagement. Your API docs? They're optimized for clarity, completeness, and literal truth. That makes them the most powerful AI marketing asset you have—and most companies don't realize it.

When OpenAI launched ChatGPT's Shopping Assistant in December 2024, the tech press focused on "ChatGPT can buy things now." We saw something more important: a public demonstration of exactly how AI models make recommendations, and how brands should approach them more like a human influencer to persuade rather than a search engine to be gamed.

Enterprise software gets recommended by default—there's decades of web presence to crawl. But when a buyer asks ChatGPT for tools in your category and you're six months old, you're invisible. The model simply doesn't know you exist. This is the real problem most AEO tools miss: it's not about ranking, it's about discovery.

Most brands think AI visibility is a single problem: show up more often in AI responses. But recommendation actually requires clearing two sequential hurdles, each demanding its own strategy. The first is visibility—getting into the conversation at all. The second is specificity—being the recommendation when constraints tighten.

Last year, over 700 million conversations happened across AI chatbots about purchasing products. Those weren't searches—they were consultations. Something fundamental is shifting in how people make buying decisions, and it looks a lot less like googling and a lot more like asking a trusted friend for advice.