Show IH: I noticed ChatGPT never mentioned my product, so I built a tool to find out why
Six months ago, I searched "best tools for quality management" on ChatGPT.
My product wasn't there. My competitor was cited three times.
I didn't have a content problem. I had a visibility problem. AI was pulling its recommendations from Reddit threads and Hacker News discussions I had never touched.
So I started manually tracking which community threads were shaping AI answers in my space.
It was 3 hours of work. Every. Single. Week.
I built AIRankCite to do it in under 2 minutes.
You paste your URL. It analyzes your category, generates the recommendation-style prompts AI engines actually use, then finds the exact Reddit and Hacker News threads that are shaping those answers right now.
The output isn't a report, it's a ranked hitlist. Each thread gets a confidence score, citation evidence, and a tailored seeding kit: what angle to take, what to say, and an opening draft.
No spam. No automation. Just knowing exactly where to show up.
476+ founders have run a scan since launch. The most common reaction: "I had no idea this thread existed."
One user went from zero AI citations to being mentioned in 3 out of 5 recommendation queries for their niche, in under a month.
Another told me the seeding kit saved them hours of research they were doing manually on Perplexity.
First scan is completely free, no credit card, and results in under 2 minutes.
Happy to answer questions below. Also curious: has anyone here been doing this kind of AI citation tracking manually? Would love to know your process.
Notice: I build CiteMePlz, a website similar to yours.
I tried to scan a website using your tool airankcite, and it didn't work (now I get error message "your account has hit a usage exhausted" so it probably wasted my free tiral).
Also, I checked your "tally so full deep scan" and it looks like Reddit thread upvote and comment counters are fake in your report. Not sure if it's done on purpose, but at least mention that it is not a real report or that some parts are invented.
Otherwise the website looks beautiful and I really like your "AEO Fix Kit" tab, that's very useful!
I can totally see how manually tracking citations would be a huge time sink. I actually know a few indie hackers who actively market their products and track AI citations, and they'd likely be happy to answer your questions about their process.
That would be amazing - I'd love to connect with them. The manual tracking pain is exactly what pushed me to build this. Most founders I've talked to either don't track at all (and have no idea where they stand) or spend hours checking prompts one by one across different models.
If any of them want to try a free scan and compare it to their manual process, I'd genuinely value their feedback on what's missing or could be better. Happy to jump on a quick call too if that's easier.
The members of "replyz" could help you with this. The whole idea is that you can connect directly with the exact type of people you're looking for and get thoughtful responses from them. You just describe who you want answers from and ask your question. Since it's community-driven, people are also encouraged to share their own experiences and insights with others too.
Appreciate the suggestion, but this is a different problem. AIRankCite isn't about getting human replies or community feedback. It's about tracking whether AI engines like ChatGPT, Perplexity, and Claude organically recommend your product when users ask relevant questions. That's a distribution channel, not a conversation.
The tool scans 5 AI engines, shows your citation status, source threads driving those citations, and gives actionable steps to improve visibility. It's more like an SEO tool for the AI era than a community platform.
One angle worth testing is whether the model even has a clear category hook for your product, not just whether it "knows" the brand. In my own tools, vague positioning tends to lose to competitors with boring but explicit comparison pages, use-case pages, and docs. Your tool could be really useful if it shows which source gaps or prompt patterns cause the omission.
You're onto something. We're actually working on that layer - showing not just which threads are cited, but WHY certain products get picked over others in the same thread. Early patterns we're seeing: products with explicit comparison pages, structured FAQ content, and community-generated 'vs' threads get cited way more than products with just a landing page. The source gap is often a content gap.
The product is useful.
What you’ve built is less “AI SEO tooling” and more visibility infrastructure for the AI recommendation layer.
That distinction matters, because AIRankCite sounds like a feature.
It explains what the tool does, but it still reads like internal growth tooling instead of the system teams rely on once AI search becomes a real acquisition channel.
That category will get crowded fast.
The products that hold position usually sound more like infrastructure than tactics.
Exirra.com fits best here.
It feels sharper, more durable, and much easier to grow into as the product expands beyond citation tracking.
Xevoa.com is the other strong fit.
Cleaner, broader, and better suited if this becomes the operating layer for AI visibility rather than just prompt citation discovery.
Fair distinction, and you're right that AIRankCite reads like a feature name. That's exactly the positioning I'm pressure-testing right now.
The infrastructure framing resonates more as the product expands beyond citation tracking into full AI visibility ops. Exirra and Xevoa are both on the list. Leaning toward testing the narrative shift first before committing to a rebrand, since the domain is the last thing to change, not the first.
Curious what made Exirra feel sharper to you over Xevoa. Platform ambition or just the sound of it?
Exirra feels stronger because it carries more weight.
Xevoa is cleaner and broader.
Exirra sounds more like infrastructure with judgment behind it.
For what you’re building, that matters.
If the product stays closer to:
AI visibility tooling
Xevoa works
If it becomes:
the system teams rely on to understand, monitor, and defend visibility across AI surfaces
Exirra carries that weight better
Xevoa feels lighter.
Exirra feels more like something teams trust to make decisions from.
Yes, manually and badly. Every couple weeks I check ChatGPT for "free Statuspage.io alternatives" , "best free status page" and just eyeball which 4-5 names show up. Same names every time. StatusPageBuddy (mine) is never one of them.
The Reddit/HN identification piece is the part I'd actually pay for my Reddit account is shadowbanned so I can't even reverse-engineer which threads are influencing the answers. Quick question: does the "seeding guidance" output point to specific threads to engage in, or is it more about content angles to pitch?
Will run a scan and report back.
It points to specific threads, the actual Reddit and HN URLs that LLMs are pulling from when generating recommendations in your category.
So you can see exactly which conversations are influencing the answers and decide whether to engage, create a counter-thread, or get mentioned in a similar one.
The seeding guidance layer then tells you what to say and where. Not just angles, but word-for-word comment copy you can drop in.
Given your Reddit account is shadowbanned, the thread identification piece alone is valuable. You can use a secondary account or post on HN instead.
Run the scan, would love your feedback.
That's exactly the layer I was hoping was there. The "which Reddit/HN threads LLMs pull from" piece is the leverage point , once you have the URLs, a counter-thread
or strategic comment is a 30-min job, not a 30-day SEO campaign.
Running the scan today, will report back.
One question while I prep: SPB is in a sparse category (free indie status pages competitors are mostly self-hosted upptime forks, not active Reddit/HN discussions). When there's basically nothing to identify, does the seeding guidance still produce output, or does the empty set itself become the signal ("go create the first mention here")? Curious whether your customer profile skews "crowded category, defend share" or "empty category, seed first."
The empty set is the signal, and that's actually the more actionable output for a sparse category.
When the scan surfaces little to nothing, the seeding guidance shifts from "engage here" to "create the canonical thread." You're not competing for position in an existing conversation, you're writing the conversation that will get cited first. That's a different brief but the tool still produces it.
For SPB specifically, a well-constructed HN "Ask HN: best lightweight status page for indie projects" thread that you seed early becomes the reference point LLMs pull from for that query. Empty category, first-mover advantage, lower effort than fighting for share in a crowded one.
To your question on customer profile: both segments are real but the empty category user needs a different frame. Less "here's where your competitors are winning" and more "here's the gap you can own." The scan output reads differently but the value is higher in sparse categories if you move fast.
Curious what the scan returns for SPB. Would love to see whether it surfaces anything or comes back thin.
Yeah, "create the canonical thread" is a much sharper frame than "engage" that's exactly how the W2 SPB signups landed (asset accumulation in an empty category > competing for share in a crowded one). Stealing the phrase.
Ran the scan on StatusPageBuddy. Three takeaways, mixed:
Genuine win: scan surfaced "Statsy" — a direct competitor I had no idea existed, positioned almost identically to SPB . Competitor discovery as a side effect of citation hunting is a real feature.
Framing tension: my exported report contained the 3 Reddit threads + relevance scores, but no actual LLM testing — no "which models mention you, where, vs gaps." The "AI citation" name primed me to expect that audit; what the tool actually delivers is "Reddit opportunity finder + comment generator." Both useful, but different value props. The dashboard's generated comments felt on the generic side ("StatusPageBuddy is a lifesaver"-style) — would get flagged by any subreddit mod with a pulse if posted from a 0-karma account. Happy to expand on this — IH DM works.
Quality nit: 1/3 threads was in r/JellyWatch_EmbyWatch (Jellyfin sub, mascot designer ask, "status page" was parenthetical). Confidence rated it "medium" (score 45) which is correct, but raising the floor to ~60 would cut the noise without losing signal.
This is exactly the kind of feedback I needed. You nailed the framing tension - we're shipping a fix today that separates results into 'Threads Mentioning You' (actual citations) vs 'Top Opportunities' (where you should be). That should make the value prop clearer.
On the generated comments: you're right, the 'lifesaver'-style copy is too on-the-nose. We're reworking the content generator to produce more value-first, subtle angles - think 'sharing what worked for me' rather than 'this tool saved my life.' Would love to DM you a before/after when it's ready.
On the confidence floor: raising to 60 is a good call. We're at 40 now, bumping it up.
The competitor discovery angle is interesting - a few users have mentioned that as the unexpected win. Might lean into that more in positioning.
Appreciate the depth here. Happy to chat in DMs.
Glad the framing helped — your three moves all sound right.
Two adds since you mentioned the competitor-discovery angle:
Got my 4th user this morning — founder of an edge-compute platform in Germany. He didn't find me via my dev.to article or this IH post. He found me via the awesome-status-pages GitHub list. Asset network discovery, zero direct outreach. If your data shows users discovering 2-3 unexpected competitors via the threads, that's probably the strongest pivot wedge — most founders deeply underestimate how non-search-first their actual pipeline is.
If you want a guinea pig for the new "threads mentioning you" tab — I run StatusPageBuddy (www.statuspagebuddy.com), still invisible to ChatGPT for "free status page tools." Happy to be a dogfood account.
Easiest follow-up channel for me is [email protected] looking forward to the before/after.
Congrats on user #4 - and the asset network discovery point is sharp. Most founders assume growth comes from search or direct outreach, but "found via a GitHub list" is exactly the kind of non-obvious distribution that compounds.
The competitor-discovery angle is interesting. We're seeing that too - users scanning their own product and finding competitors they didn't know existed in the same threads. That "who else is being recommended alongside me?" view is something I'm building out more.
On the guinea pig offer - absolutely, I'd love that. Run a free scan on statuspagebuddy.com at airankcite.com and let me know what comes back. I'll also run one on my end and share the full results with you at [email protected]. Especially interested in whether the "invisible to ChatGPT" gap shows up clearly in the AI Citation Check section.
Thanks for the offer - real usage data from a product in the wild is worth more than any internal testing.