A few weeks ago I shared an early version of MentionedBy.ai — a tool we built to monitor how your brand is mentioned inside AI-generated answers from ChatGPT, Claude, Gemini, Perplexity, and other LLMs.
We’re now officially live
This started from our own frustration. Our startup wasn’t being mentioned in ChatGPT responses, even for queries where we were clearly relevant. Meanwhile, legacy or SEO-heavy brands kept showing up. We realized: AI is becoming the new search engine — and no one knows how they rank in it.
So we built MentionedBy to answer questions like:
How often does your brand appear in AI-generated answers?
Is the mention accurate or hallucinated?
Are you being misrepresented, dropped, or out-ranked by competitors?
What’s your sentiment score across different LLMs?
How do your rankings change over time?
Under the hood:
We run scheduled and real-time prompts via OpenRouter and native APIs
Cluster and semantically match results using OpenAI + Cohere
Log all responses in a time-series DB for trend tracking
Run hallucination detection by comparing AI claims with verified sources
We’re calling this space Answer Engine Optimization (AEO) — like SEO, but for LLMs.
Would love your feedback — especially on how we can make LLM visibility more transparent and actionable. AMA about the stack, prompt orchestration, hallucination detection, or what we’ve learned comparing LLMs.
—
Nikin
Founder @ Synapse AI Labs
Built in Sri Lanka, Global by default.
We’re now officially live
This started from our own frustration. Our startup wasn’t being mentioned in ChatGPT responses, even for queries where we were clearly relevant. Meanwhile, legacy or SEO-heavy brands kept showing up. We realized: AI is becoming the new search engine — and no one knows how they rank in it.
So we built MentionedBy to answer questions like:
How often does your brand appear in AI-generated answers?
Is the mention accurate or hallucinated?
Are you being misrepresented, dropped, or out-ranked by competitors?
What’s your sentiment score across different LLMs?
How do your rankings change over time?
Under the hood:
We run scheduled and real-time prompts via OpenRouter and native APIs
Cluster and semantically match results using OpenAI + Cohere
Log all responses in a time-series DB for trend tracking
Run hallucination detection by comparing AI claims with verified sources
We’re calling this space Answer Engine Optimization (AEO) — like SEO, but for LLMs.
The platform is live: https://mentionedby.ai
Would love your feedback — especially on how we can make LLM visibility more transparent and actionable. AMA about the stack, prompt orchestration, hallucination detection, or what we’ve learned comparing LLMs.
— Nikin Founder @ Synapse AI Labs Built in Sri Lanka, Global by default.