LLM Insight
Track & optimize how AI search engines talk about your brand
6 followers
Track & optimize how AI search engines talk about your brand
6 followers
LLM Insight monitors how ChatGPT, Gemini, Perplexity, and Google AI Overviews mention your brand. Track citation rates, analyze source domains AI pulls from, and get actionable recommendations to improve your visibility in the new AI search landscape.
Payment Required
Launch Team / Built With
Render: Get up to $100K in startup creditsThe fastest way to launch and scale your startup in the cloud
Promoted
Congratulations on the launch!
A lot of teams are still celebrating stable SEO rankings while traffic quietly declines, and AI answers are probably a big part of that. I like that LLM Insight focuses not just on mentions, but also on citation sources and actual organic impact. That makes it easier to justify action internally.I'm curious how you handle variability in AI responses. Since models like ChatGPT and Gemini can generate different answers for similar prompts, do you run multiple prompt variations to calculate mention rates more reliably?
@naveed_ratansi
Great question — and honestly, this is one of the hardest parts of building in this space.
You're right that AI responses are non-deterministic. The same query can produce different answers depending on timing, phrasing, and even session context. A single snapshot tells you almost nothing.
Our approach has a few layers:
Multiple prompt variations per query category. For each topic we monitor, we don't just run one prompt — we test a range of natural phrasing patterns (e.g., "best CRM for startups," "top CRM tools," "which CRM should I use," etc.). This gives us a more realistic picture of how real users would encounter your brand.
Repeated sampling over time. We run these queries on a regular cadence, not as one-off checks. This lets us calculate mention rates as a statistical trend rather than a single data point. A brand showing up in 3 out of 10 queries today vs. 6 out of 10 next month — that's a meaningful signal.
Cross-model comparison. Since each AI model (ChatGPT, Gemini, Perplexity, Google AI Overviews) has different retrieval mechanisms and training data, we track each separately. A brand might be well-cited on Perplexity (which pulls live sources)
but invisible on ChatGPT. That gap itself is actionable insight.
Happy to dive deeper into the methodology if you're interested!