Built a tool that finds which Reddit/HN threads are making ChatGPT recommend your competitors
AI answer engines like ChatGPT, Perplexity, and Claude don't pull product recommendations from thin air. They pull them from community threads, Reddit discussions, HN posts, and niche forums where founders and users have already debated the best tools in a category.
Most founders have zero visibility into which threads those are. So they post randomly, hope for the best, and wonder why competitors keep showing up in AI answers instead of them.
AIRankCite fixes that.
You paste your product URL, and it returns a ranked hitlist of the exact Reddit and HN threads currently shaping AI recommendations in your niche. Each result comes with a confidence score showing how much weight that thread carries, plus a tailored seeding kit with word-for-word comment copy you can drop in to start shifting the AI narrative toward your product.
It tracks ChatGPT, Perplexity, Claude, Gemini, and Copilot. Full scan takes under 2 minutes.
Free first scan at airankcite.com
Curious what others here are doing for AI citation tracking. Is this on your radar yet or still too early for most stacks?
Smart positioning. One axis I'd love to see surfaced: not all citations are equal-weight in actual purchase decisions.
LLMs heavily prioritize threads where the recommendation answers a specific buying-stage question ('looking for X to do Y under €Z') vs. generic 'best Y tool 2026' lists. The former show up in real purchase-intent prompts, the latter mostly inflate visibility scores without converting.
Does AIRankCite differentiate between these in the visibility lift metric, or are all mentions weighted the same?
This is on my radar but I think the playbook breaks differently for non-English markets and it's worth flagging.
We're building an email/CRM/voice product for European SMBs. When I asked ChatGPT and Perplexity in French "meilleur logiciel email IA pour PME francaise" the recommendations are wildly thin - mostly translated US tools with bad French support. Almost nothing surfacing from French startup forums because those communities are smaller and AI engines weight English Reddit threads disproportionately.
My current hypothesis: for non-English builders, the citation game has two halves. Half 1 = English threads (Reddit, HN, IH) where you compete with everyone. Half 2 = local-language forums where you can dominate fast because incumbents ignore them. The local half pays off in 6 months when AI engines catch up to non-English content (already happening with Mistral and Claude in French, faster than expected).
Question for you: does AIRankCite handle non-English citation sources well? Specifically curious if you crawl French and German tech forums and weight them appropriately, or if you're English-Reddit-first like most tools in this space. That's the gap I'd pay for.
Going to run a scan on our domain.
This is one of those products where the wedge is stronger than the current name.
The real value is not “AI citation tracking.”
It’s competitive narrative control.
Founders are not paying to see which Reddit thread matters.
They’re paying to understand why competitors keep getting recommended and how to change that before it compounds into distribution loss.
That’s the real product.
AIRankCite explains what it does.
It also traps it in a narrow SEO/tooling frame.
If this expands beyond “find citations” into “shape recommendation share,” the product likely outgrows the current name fast.
Exirra.com fits that direction much better.
Sharper, more defensible, and broad enough to hold a larger competitive intelligence layer once this becomes less about tracking citations and more about controlling category narrative.