How OnFabric (EF S24) Became Discoverable in an Emerging AI Category
An Entrepreneur First–backed startup defining a brand-new category — the digital self for AI — partnered with Attensira to shape how AI models describe and recommend them before the space became crowded.
“OnFabric is building the digital self for AI, and Attensira makes sure it's discoverable in AI search.”
OnFabric is defining a new category: a persistent digital self that AI assistants can call on for identity, context, and preference. Defining a new category is the hardest possible go-to-market — AI models don't have a clean mental model of the space, there are no review sites yet, and buyers don't have a keyword for the problem. OnFabric used Attensira to understand how ChatGPT, Claude, and Perplexity were already talking about adjacent concepts, to shape the language around their category, and to make sure the first wave of AI-assisted research surfaced OnFabric accurately.
The challenge: defining a category AI has never heard of
When a startup is defining a new category, the usual SEO playbook doesn't apply. You can't rank for a keyword nobody searches for yet. You can't buy ads against intent that doesn't exist. What you can do is shape how AI models describe the adjacent space — identity for agents, memory for assistants, personal context layers — and earn the right to be the brand AI names when a buyer first articulates the problem. For OnFabric, getting that language right was mission-critical.
How OnFabric used Attensira
OnFabric started by monitoring how ChatGPT, Claude, and Perplexity answered early-signal queries — questions about personal AI, agent memory, user profiles for assistants, and persistent preferences across tools. Attensira surfaced the exact vocabulary each AI model was using, which brands (if any) were associated with the space, and where there were citation gaps. That intelligence turned into OnFabric's messaging architecture: the way they named product concepts, the comparison points they emphasized, and the technical documentation they prioritized. Every page was structured to teach AI models what OnFabric is, what problem it solves, and why it matters.
The outcome
OnFabric is now showing up in AI answers for the adjacent queries its ICP is starting to ask — identity for AI agents, personal context for assistants, memory infrastructure — often alongside much larger incumbents. By shaping the language early, OnFabric built a moat that pure ad spend can't buy. When a buyer eventually articulates the problem directly, OnFabric is one of the first names AI reaches for.
“If we waited to be indexed by Google, we'd be late. AI search is where our category will be defined. Attensira is how we make sure we're part of that definition.”
The repeatable AI visibility playbook
Steal this exact sequence for your own startup.
- 1Find the adjacent queries AI already answers — the problem space around your new category.
- 2Map the vocabulary each AI model uses for the problem and the incumbents it associates with it.
- 3Shape your messaging so AI can accurately describe your product in that context.
- 4Invest in docs, technical explainers, and comparison pages that teach AI what you do.
- 5Track weekly how AI describes your category — iterate on language that isn't landing.
- 6Compound. Being early in an AI-defined category is worth more than being first on Google.
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