VisibAI
AI visibility, generative engine optimization, GEO, AI SEO, ChatGPT visibility, brand monitoring, LLM optimization, AEO, AI search, competitor tracking
About
VisibAI is a B2B SaaS platform that measures and improves how your brand appears in AI-generated answers. As people increasingly ask ChatGPT, Perplexity, Claude, and Gemini for recommendations instead of running traditional Google searches, the brands those models name are the ones that win attention. VisibAI tells you exactly where you stand.
The platform runs dozens of industry-specific and location-specific queries across up to six AI platforms (ChatGPT, Perplexity, Claude, Gemini, Mistral, You.com), then returns a single visibility score out of 100. Beyond the headline number, it surfaces which competitors are appearing in AI answers when yours isn't, identifies the specific gaps holding you back, and generates a prioritized fix list plus an AI action plan to close them.
VisibAI is built for the shift from SEO to Generative Engine Optimization (GEO). It serves three audiences: agencies managing visibility for multiple clients (with white-label subdomains and branded reports), in-house brand teams tracking their presence over time, and small businesses that want to understand and improve how AI describes them.
Free tools include an llms.txt generator, an AI crawler checker, and a robots.txt checker. Paid tiers add competitor tracking, monthly re-scans, multi-platform coverage, and agency white-labeling.
Built in the EU with GDPR-compliant infrastructure, VisibAI runs on a high-margin model with audits costing cents to produce. The goal is simple: make sure that when AI talks about your industry, it talks about you.
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FounderPlaybooks.
What other founders did to grow.
2722 dispatches from hundreds of founders, pulled from the week's best podcasts.
the biggest win that we had on our side was just we stripped out an entire pricing tier we switched over to be able to communicate with the amount of hours that you spend to be able to play great content... beginning to abstract away from a lot of the fine-tuned details that go into an AI model
Price in listening hours not tokens: abstract AI complexity away from consumers
ElevenLabs Reader's biggest win was collapsing a complex multi-tier pricing structure into a single price denominated in listening hours, completely removing references to tokens, credits, and model tiers. Consumers buying an audiobook experience think in hours of listening, not in AI compute units. The internal cost model is an implementation detail — hide it entirely and price around what users actually care about.
to create a truly viral video you have to understand what your viewers want to see which you have to ask yourself like who are your viewers what are their interests what are they currently watching why are they watching it and how can you create content even more engaging than what they're currently watching
Ask Users For Their Instagram Handles And Reverse-Engineer Who They Already Follow
David argues the highest-leverage research is understanding what your users already watch. He asks users for their Instagram handles, then mines who they follow to find influencers worth sponsoring and content formats worth copying.
There's a play for whatever you're stuck on.
Read all 2722 playbooks