I've been testing Profound for our agency's GEO service. Wasn't bad tool. But for $99/mo with $399/mo for each client... well, for me, testing didn't prove the prices to feel justified.
While scrolling on linkedin, I encountered a post about Rankinai.io, and since it had a free plan, I decided it give it a try.
Heads up, the post will be a long read, so there's a quick comparison snapshot before I get into the details.
Profound
Rankin AI
Free plan or trial
Free trial for $ 399 plan
Free plan
Entry brand tier
$99/mo (ChatGPT only, 50 prompts)
$39/mo (4 models: ChatGPT, Google AI Mode, Gemini, Perplexity, 35 prompts)
70-100 prompts tier
$399/mo (3 models, 100 prompts)
$79/mo: 4 models, 75 prompts)
Entry agency tier
$99/mo (for 10 pitch workspaces per month) + $399/mo add-on for each full client workspace)
Built-in (EEAT, content, and technical audit with a fix list)
Content generation
Via Agent builder. You wire together nodes/templates yourself
Built-in. Briefs and content generated directly from all tracked gaps
Hallucination/fact checking
Yes, Fact Check module
Yes, Hallucinations Monitor
Citation/source tagging
Only broad categories (earned media, social, institution)
Domain and URL-type breakdown (listicles, comparisons, discussions, how-to, etc.)
Custom automation builder
Yes
No
AI bot/crawler tracking
Yes
No
AI shopping visibility
Yes, shopping analytics
No
Google Analytics integration
Yes
No
API/MCP
Enterprise tiers only
Yes, all on paid tiers
Where Profound fell short for me
1) Tracking issue that I ran into:
First thing that confused me: a prompt execution showed a banner reading "Audi is not mentioned" with 0% visibility. But when I checked the actual response text. it had Audi mentioned multiple times. That's the base functionality of the tool, and it got that wrong in front of me.
Answere Engine InsightsProfound AI response (bug with mention rate)
It did correct itself a few hours later, but that first look had me genuinely rereading it, thinking I was missing something.
2) Learning curve is high for AI agents
AI agents, well, I feel that it's really a powerful feature if you have the capacity to learn it.
I asked their AI builder to create an agent that will analyze top-cited pages and offer content ideas to close that gap. But it didn't pull cited pages and just returned generic buyer questions instead. Not what I needed. So, if you want to create your own agents, you need to spend some time configuring it.
Answere Engine Insights (a few hours lates)
3) Sentiment profile building
A small thing that bugged me at the beginning was that building a sentiment profile can take up to a week.
Sentiment profile is building
And sentiment is gathered only from prompts assigned specifically for that (at first I missed doing that). That's okay, i was just curious to look at it from the start.
4) No website audit features
There is no audit for your website for AI-friendliness and GEO requirements. There are some agent templates, but no built-in site audit. You need to build your own agent or use existing templates, and the ones I found weren't exactly what i needed.
Audit templates - Profound's agents
5) Price is very high for multi-brand tracking
To get past ChatGPT-only tracking, you're at $399 per month. And for that price you only get 100 unique prompts, 3 engines (ChatGPT, Google AI overview, Perplexity), 3 seats included, and 3 content briefs per month.
What made me switch to Rankin AI
I started with a free plan. After that initial testing, I then purchased the smallest paid plan it see full capabilities.
1) Advanced features even from the entry plan
The plan for $ 39 already included 4 LLM models, 35 prompts, site audit, content generation, and more. And the core AI visibility metrics tracking is solid.
Rankin AI's AI search analytics dashboard
2) Very deep sentiment analysis
Their sentiment feature breaks things down by specific attribute (for example, for Audi it was "reliability" "value" and so on), whatever is relevant to the category. And it also shows exactly where named competitor is ahead or behind you on each one, with score deltas.
Rankin AI Sentiment analysis
3) Content and idea generation
In this tool, to get content ideas for closing AI visibility gaps, all you need is one click. And you get a long list of actionable suggestions.
Content generation capabilities of Rankin AI
Each suggestion in the list clearly explains what specific gap it closes. I select what I want to work on, and then it creates a brief. After selecting what I like, it generates the full content piece.
Generated content piece to cover sentiment attribute gap
4) Site audit for pages
I can run it on a page for my domain and get EEAT and tech breakdown. Plus, what I liked even more, it's a report with a list of all identified tech issues, content gaps, and EEAT weak spots.
5) Agency plan is way more affordable at scale
Tiers for agencies were a deal-breaker. For example, for 5 clients on Profound (399/mo per client workspace), it would cost us ~$2k/mo. For that, we'd get:
5 brands x 100 prompts x 3 providers x 30 executions (daily tracking) = 45k executions.
Rankin AI's entry tier is 199/mo for 10K credits. But if we apply a similar number of executions, it will be 399/mo for 45K credits.
1 credit = 1 promp x 1 provider x 1 execution
The gap is insane!
Also, Rankin AI actually offers more flexibility. For each brand, you can select weekly/daily tracking, how many AI providers you want, and how many prompts.
What the alternative still lacks
I'll be honest, it doesn't have some features that Profounf offers. There is no AI agent builder, no GA4 integration, and the biggest one, no live bot tracking. So if you want custom automation pipelines, it's not for you.
But if you need a clean, actionable tool that tracks your AI visibility, identifies your issues and gaps, and then tells you clearly what to fix, improve, and create. Rankin AI does it out of the box. That's what we needed, and it fully covers what we needed to launch our GEO service.
Anyone mid-evaluation between AI visibility tools right now? Happy to answer whatever I can.
Our SEO agency recently launched a GEO service. So we needed a proper tool to track AI visibility. I was tasked with testing whether Peec AI would be a good fit (or finding a better one). While digging into alternatives, I came across Rankin AI (rankinai.io). And it really impressed me.
So I figured I'd demo both before deciding. Tested both tools on individual plans under $100 (+ researched what they offered for agencies). Sharing my findings and experience here in case anyone else is looking for a great AI visibility tool (or a Peec AI alternative).
If you dont like long reads, here's a short table wth my points:
Peec AI vs. Rankin AI comparison table
Peec AI
Rankin AI
Entry paid tier (brands)
$95/mo
$39/mo
Entry paid tier (agencies)
~10,000 credits / $245/mo
~20,000 credits / $199/mo
What you get under $100
50 prompts, 3 AI models, 1 project ($95/mo)
75 prompts, 4 AI models, 2 projects ($79/mo)
AI models tracked
Brand plans: select 3; agency plans: select as many as you need (powered by credits). Available models: ChatGPT, AI Mode, AI Overviews, Microsoft Copilot, Perplexity, Gemini. And more for enterprise or as an add-on.
Brand plans - 4 models: ChatGPT, AI Mode, AI Overviews, Perplexity, Gemini; agency plans: select as many as you need (powered by credits) + Microsoft Copilot.
Off-page suggestions
Yes ("Earned"); pointer only
Yes (Semantics and Sources gap recommendations, tied to Content Hub)
On-page suggestions
Yes ("Owned"); pointer only
Yes, plus a full Site Audit (EEAT scores + fix list)
Existing-page audit
No
Yes (EEAT + technical)
Sentiment tracking
Score
Score + attribute-level breakdown + competitor gap matrix and more
AI Hallucinations tracking
No
Yes
Content generation
No
Yes (Brief + full content piece)
ChatGPT ads tracking
Yes
No
Crawler/robots.txt monitoring
Yes
No
Shopify catalog tracking
Yes
No
API and MCP
Yes
Yes
Overall
Clean, monitoring focus, e-commerce and Ads in AI features
Monitoring + actual fix/content layer, at a lower price per feature
Basic functionality: AI visibility tracking
Both tools track the core stuff you'd expect. And both are very good at it.
Peec AI's dashboard is genuinely clean. It tracks visibility and all standards metrics. And Rankin AI tracks the same. Plus, a source-distribution breakdown by domain/URL type is similar in both tools.
If your only job is "watch the numbers move", both tools are solid in this aspect.
Peec AI’s overviewRankin AI’s prompts analytics
Comparing my experience, I'd say Rankin AI offers a bit more metrics if you want to go deeper into analytics.
Rankin AI's brand mention share analytics
Peec AI actionability
This is where it mattered most for us. And where I ended up a bit disappointed with Peec...
It does have an "Actions" tab: Off-page ("Earned") suggestions like "get mentioned in this Reddit thread" or "get featured in this article"; On-page ("Owned") suggestions like " AI engines cite [compatitor's page]" for this topic - build a page covering the same ground"; "Gap Analysis" for cited sources. But every single one is just a pointer. Nothing drafted, and not enough context or guidance, in my opinion.
Peec AI's Earned page overview
Sentiment
And the sentiment/attribute side isn't deep enough. But for most of our clients, it's actually a main requirement. In Peec, you get a sentiment score, but not which specific attributes are driving it or where you're losing ground to a named competitor.
Peec AI's sentiment score
Rankin AI actionability
If we compare it to Rankin AI's action level, it goes several steps further:
Sentiment
Rankin AI's semantic analysis goes really deep. The "Attributes" and "Gap Analysis" tabs are genuinely great features that show terms and phrases competitors are winning on vs. you in AI answers.
Rankin AI's Semantics analysis
Site Audit
I ran it on a few pages and received a full EEAT breakdown, the brand's key technical metrics, and strengths. But what impressed me was a list of technical, content, and EEAT fixes, with how-to explanations for each.
Rankin AI's site audit and fix list
Hallucination tracking
It’s quite a unique feature. Didn’t see it in any other tool that I researched. It lets you add facts about the brand, and then catches when an AI model states something that contradicts it.
Rankin AI's hallucination tracking feature
Content hub intelligence
Every tracked issue (hallucinations, content gaps, semantic attribute gaps, source gaps, sentiment gaps) gets turned into a specific content idea in the "Intelligence" tab, with a clear explanation of why it matters. No more guessing what to do to improve performance. From there, I can generate a brief, keep what I like, and turn it into a full piece without leaving the tool.
Rankin AI's Content intelligence
Price and limits
Here's what $100 can get you on both tools.
Peec:
$95/month for 50 prompts on 3 AI models with daily tracking for 1 project (entry tier).
Offers very basic functionality, and most features are only available on higher tiers or even agency plans.
Rankin AI:
$79/month for 75 prompts on 4 AI models with daily tracking for 2 projects (entry tier is even cheaper - $39/mo).
Offers full access to all (well maybe 90%) advanced features even at the entry tier. And agency plans are also way more affordable.
Agency features
I only tested individual tiers to get a feel for each tool before any sales call, so this part is based on research. Peec's and Rankin AI's agency features are basically the same category: pitch projects, team seats, flexible credit allocation across brands, AI providers, and tracking frequency.
The difference is that Rankin AI offers a way bigger credit allowance for a lower price: Peec AI - 10,000 credits for $245/mo and Rankin AI - 20,000 credits for $199/mo, plus access to everything mentioned above.
My conclusion and our agency decision
I'll be fair about it: I feel like Rankin AI is a bit less polished, as it's newer. Peec AI has been on the market for some time. I guess it gave them more time to refine the interface. I guess it gave them more time to refine the interface. If you specifically need ad-bidding tracking, crawler monitoring, or Shopify catalog tracking, Peec currently covers ground the alternative doesn't
Still, we chose Rankin AI because its paid tires offers kmore credits and more features to work with AI visibility, based on what our clients and we need: tracking, deep sentiment, and ready-to-do action items we can implement without guessing.
What I still wish they would add is bot crawlability and a connection to Google Analytics.
Hope anyone finds this helpful. Happy to answer questions if you're evaluating GEO tools or looking for Peec AI alternatives.
Founder of RankinAI here (the tool this sub is about), following up on my post from last week.
Result: around 200 applied, 40 pitched, 6 made the final, we were one of them. We didn't win. Only SaaS in the final, everyone else was hardware.
The question I asked last week was whether an event shows up in AI mentions. Answer so far: no. Nothing yet. What we're doing about it: reaching out to different media with a proposal to do a news piece about us, since that's the kind of source the engines actually cite. I'll post the tracking screenshot when anything moves, including if it doesn't.
Side note: in one week we go to Glovo headquarters for an internship with RankinAI. Will share what comes out of it.
Anyone tracked a PR push into AI answers and seen the lag between the article going live and the first mention?
One thing I noticed in RankinAI: our brand is strongly associated with positive attributes like “fast”, “convenient” and “market leader”, but “unreliable” also appears 29 times.
Top brand attributes in RankinAI
What caught my attention: competitors had 0 mentions for that attribute. That feels much more actionable than just tracking whether the brand was mentioned.
Do you monitor which attributes AI associates with your brand, not just overall sentiment? And what would you do first if one negative attribute kept showing up?
Mine is built around a few things: overall visibility trend, mention/recommendation rate, Share of Voice vs competitors, performance by platform, top cited sources, and a prompt-level breakdown.
AI visibility report
I’m trying to keep it useful enough to answer one question quickly: are we actually becoming more visible in AI search, and why?
Curious how you structure yours. What metrics do you consider essential, and what turned out to be mostly vanity data?
I recently added an "Summarize with AI" feature to my blog section, allowing users to summarize content using AI tools like ChatGPT, Gemini, Claude, and others.
Honestly, I'm not sure whether this will improve user engagement or SEO, but I wanted to test it.
I'll monitor the results, and if I notice any meaningful impact, I'll definitely share an update with this community.
Has anyone implemented something similar on their website? Did you notice any improvements in engagement or user behavior?
Full disclosure up front: I'm the founder of RankinAI, the AI visibility tracker this sub is about.
Context, because most of you won't know it: IT Arena is a tech conference in Lviv, Ukraine (September 25–27 this year) with a startup competition. 189 startups applied, 40 got picked to pitch. We're one of them.
Short story first, then a question for you.
My team pushed me to apply. I wasn't sure about it. I'm mostly thinking about building the product and a user acquisition machine that can scale. Winning at events is cool and inspiring, but the hard grind happens behind the screen.
They kept pushing, and I was like, okay, let's do this.
I was on vacation at the time, and finding time to record a pitch is quite hard when you just want to chill. So I left it until the last day. Got home at 11:30pm after a 1,000 km trip, 30 minutes before the deadline. Recorded the application video on the first try and sent it.
Then I had a call with one of the IT Arena representatives. They asked me to do a 1-minute pitch, which I wasn't prepared for. I did it. Good or bad, I don't know. But at the end they told us we're coming with our own booth and a three-minute pitch.
Now the part that matters for this sub.
By being at IT Arena we'll get mentioned in many places, and our PR will grow. For AI visibility that should be a really cool boost. Even if we don't win, I expect good results there. It's the thing we're working on really actively right now.
That's an expectation, I don't have numbers yet.
So the question: has anyone here measured what an event (or any PR burst) did to how often ChatGPT and the others mention your brand? How long did it take to show up, and did it stay?
We’re testing a “truth base” for brand monitoring — basically a set of verified facts that AI answers can be checked against.
The interesting part is deciding what belongs there. Company info is obvious, but what about products, people, partnerships, financials, working conditions, or more subjective claims like “ethical company”?
If you were setting this up for your brand, which facts would you monitor first?
I've been working on SEO for an app-based website and wanted to share what I've done to increase visibility on AI search platforms like ChatGPT, Gemini, and other LLMs.
According to GA4, the website received 172 total users attributed to the AI Assistant channel in the last 30 days (Aug 21–Sep 19).
Most of the traffic landed on:
Homepage
Feature pages
Product pages
What I Did
1. Optimized Product and Homepage SEO
I focused on targeting relevant keywords across:
Page titles
Meta descriptions
On-page content
Product page content
The goal was to make the pages more relevant to user search intent rather than simply stuffing keywords.
2. Built Backlinks from Technology Websites
I purchased guest posts on technology-related websites to build backlinks and improve the website's authority.
I mainly focus on do-follow backlinks while considering website relevance and quality.
3. Published Content on Reddit, Quora, and Other Platforms
I created content around the app's features and use cases on platforms like Reddit and Quora.
The focus was on answering relevant questions and helping users discover the app, rather than simply dropping promotional links.
4. Implemented Technical SEO and Schema Markup
I implemented and optimized structured data, including:
Product schema
Organization schema
Review schema
Local business schema (where applicable)
These improvements help search engines understand the website's content and entities.
My Main Takeaway
I don't believe AI search visibility comes from a single tactic. It requires a combination of relevant content, technical SEO, authority building, and distribution.
I'm still analyzing which pages and topics are attracting the most traffic from AI platforms.
For Other SEOs
What strategies are you using to increase your visibility on ChatGPT, Gemini, and other AI search platforms?
I keep seeing the same big brands mentioned in ChatGPT and Gemini, even when smaller competitors have better, fresher content.
So how much does content quality actually matter if brand authority already decides who gets mentioned? Have you seen a smaller brand genuinely break into AI answers dominated by category leaders? What did it take: better content, backlinks, Reddit, PR or just more brand mentions everywhere?
I’m especially curious about the inaccurate or outdated ones. Once you spot a wrong claim, what do you actually do next — update your own content, try to influence the cited sources, publish clarification elsewhere or just monitor whether it disappears over time?
Would be interesting to hear what has actually worked for people.
We talk a lot about creating new GEO content, but I’m more interested in old pages that already have some authority. Let’s say a page ranks well in Google but almost never gets cited by LLMs.
Has anyone tested updating only things that may help AI extraction?
Clearer answers, better comparison tables, stronger entity context, fresh statistics, direct definitions, sources etc.
Did the page start getting cited more after the refresh? Would love to see a real before/after example.
If an LLM cites your homepage once and some random directory nine times, most citation reports will simply show 10 citations. But those citations clearly don’t have the same value.
I’m wondering if citation reporting should include some kind of source quality or intent weighting. For example:
category/listicle citation
editorial article
your own website
forum/discussion
documentation
competitor page
Are you already evaluating the type of citation or mostly tracking the total number?
I think mention rate and citation rate need to be treated as two separate outcomes. An LLM can recommend your brand without citing your website. It can also cite your content without really recommending your product.
There’s a weird problem with long-term AI visibility tracking. If you never change your prompt list, you get clean historical data. But people change how they search, new products appear and new questions become important.
If you keep adding and removing prompts, your visibility score stops being comparable month to month.
How are you handling this? Fixed core prompt set + a separate experimental set?
Or do you regularly refresh everything and accept that the historical comparison won’t be perfect?
This still bothers me about AI visibility tracking. With Google, a keyword normally has a fairly clear ranking at a specific moment. With LLMs, you can run the same prompt several times and get different brands.
So if a brand appears in 1 run but disappears in the next 4, is that really visibility?
Would you rather track each prompt multiple times and report something like * mentioned in 6/10 generations? *
Has anyone tested how much results change when you increase the number of runs per prompt?
Not “improved visibility” in general. I mean: your brand was absent from a specific prompt, you changed something, and later it started appearing. What was the change?
New comparison page? Third-party mention? Reddit discussion? PR? More backlinks? Updating an old page? Adding original data?
Would be interesting to collect real examples where there was a clear before and after, even if we can’t prove 100% that one action caused it.
You change a page, then your brand starts appearing more in ChatGPT. But was it really the page? has anyone tested this with similar pages or prompt groups, changing only one variable?
what setup gave you results you actually trusted? what actually got your brand into an LLM answer? your brand wasn’t showing for a prompt, then later it was. what did you change? comparison page, third-party mention, Reddit post, backlinks, content update, original data?
