AIScan
Audit whether AI engines can see, cite, and recommend your website.
Tagline
See how AI sees your site
The audit layer for AI search
See if AI recommends your brand
Audit your site for agents and models
AIScan is the audit layer for the AI search era: if Google Search Console told you how Google saw your site, AIScan tells you how ChatGPT, Perplexity, and Claude do.
This works because the product is explicitly a diagnostic tool with scores, checks, and fixes, not a generic SEO suite. It frames AIScan as a new category standard rather than just another crawler.
The only scanner that measures both technical readiness and whether AI actually recommends your brand.
The page clearly distinguishes infrastructure scores from Brand Visibility, and that distinction is the strongest product differentiator. It gives a sharper story than competitors that only audit schema or page structure.
An alternative to expensive SEO/AI search consultancies: get the audit, the evidence, and the fix pack in minutes.
AIScan's value is not just scoring but immediately actionable output: code snippets, llms.txt templates, robots.txt lines, and MCP config. That makes it a direct substitute for a consultant-led audit.
Primary user
Technical SEO lead or growth marketer at a SaaS company responsible for organic acquisition and AI search visibility
ICP #1
Technical SEO manager at a mid-market SaaS company
Pain
Traffic is flattening because ChatGPT, Perplexity, and Google AI Overviews are answering the question before the user clicks, and they have no clear way to prove why their brand is missing from those answers.
Why this solves
AIScan translates vague AI search anxiety into a concrete audit: score the site, find missing schema and crawler access issues, then measure whether AI actually names the brand versus competitors.
ICP #2
Founder-operator of an early-stage B2B SaaS competing in a crowded category
Pain
The team keeps hearing that AI assistants recommend only a few brands, but they don't know if they are invisible because of weak technical setup, poor citations, or lack of brand mention share.
Why this solves
The Brand Visibility report shows actual mention rate and share of voice across realistic prompts, giving them a direct read on whether they are being recommended or ignored.
ICP #3
SEO consultant or agency owner selling retainers to SaaS clients
Pain
Clients want an AI search strategy, but most tools only give generic SEO advice and no evidence tied to AI answers or machine-readable readiness.
Why this solves
AIScan gives a client-ready deliverable with scored findings, competitor mentions, and concrete fixes they can forward to a developer, making it easy to package as a premium audit.
Strengths
- +The page has a crisp, memorable category claim: "The AI Visibility Standard" is much stronger than generic SEO language.
- +The product is differentiated with real mechanics: 80+ checks, 30 prompts, share of voice, MCP Readiness, and x402 payments.
- +It shows actual output structure, which makes the promise feel concrete rather than aspirational.
Weaknesses
- −The page is overloaded with jargon for a first-time visitor: AEO, GEO, Agent Readiness, MCP Readiness, x402, llms.txt, Base, and on-chain payments all appear almost immediately.
- −The crypto/payment layer is too prominent for a main buyer who probably only wants to know if their site is visible to AI.
- −The messaging tries to be both developer-first and marketer-first, which dilutes the primary CTA and makes the product feel more complex than it needs to be.
- −The claims are aggressive but not fully de-risked; stats like '<5% of websites are properly set up' and '1B+ weekly ChatGPT queries' need stronger proof or softer framing.
- −The page spends a lot of space explaining the category, but not enough on who should buy first and what business outcome they should expect within 30 days.
Fix these
- Create two distinct landing paths: one for marketers focused on visibility and competitor mentions, and one for developers focused on MCP, x402, and API access.
- Lead with the Brand Visibility report for non-technical buyers, because 'who names your brand in AI answers' is easier to understand than four abstract scores.
- Reduce the upfront crypto friction by hiding Base/x402 details behind a developer section instead of placing them near the main CTA.
- Add proof assets: before/after scans, example reports from recognizable brands, and screenshots of fixes applied in real codebases.
- Tighten the hierarchy so the core promise is one sentence, one CTA, and one immediate example report before any deep explanation of AEO/GEO/MCP.
Drop-in replacement copy
Headline
See how AI sees your site
Scan visibility, brand mentions, and machine-readable readiness in 60 seconds.
Know if AI can actually find you
AIScan checks whether your site is accessible, parseable, and citeable by AI engines. You get a clear read on what is blocking visibility instead of vague SEO advice.
Measure whether AI recommends your brand
Run 30 realistic prompts and see how often your brand shows up versus competitors. This turns AI search anxiety into a number you can track and improve.
Get fixes a developer can use immediately
Every issue comes with specific next steps and copy-paste snippets. That includes schema.org JSON-LD, robots.txt guidance, llms.txt setup, and MCP recommendations.
Use one audit for marketing and engineering
Marketers get the visibility report. Developers get the implementation details. Agencies get a client-ready deliverable they can ship fast.
FAQ
Is this for marketers or developers?
Both. Marketers use it to understand visibility and competitor mentions, while developers use the fixes to implement changes.
How is this different from regular SEO tools?
Traditional SEO tools focus on rankings and traffic. AIScan focuses on whether AI systems can see, cite, and recommend your site.
What exactly does the Brand Visibility report show?
It measures how often your brand appears in AI answers across 30 prompts, plus share of voice and which competitors are being recommended instead.
Do I need to understand MCP or x402 to use this?
No. Those are included for teams that want them, but the main audit is useful even if you only care about AI visibility and brand mentions.
How long does a scan take?
About 60 seconds for the core audit. The Brand Visibility report runs separately, but the output is still quick enough to use in a real working session.
I built AIScan because search is changing fast. It scans your site in 60 seconds and tells you if AI can see it, cite it, and recommend it. Not theory. Actual checks. Actual fixes. Actual code you can ship.
I kept seeing the same problem: teams obsess over SEO, but have zero clue whether ChatGPT or Perplexity can even understand their site. AIScan turns that into a report with scores, mentions, and exact fixes. Made for people who want proof, not vibes.
AI answers are swallowing the top of search. If your site isn't crawlable, cited, and clearly machine-readable, you're losing the recommendation before the user ever reaches Google. AIScan shows exactly where that happens.
Drop in a URL and AIScan runs a full AI visibility audit: - AEO - GEO - Agent Readiness - MCP Readiness Then it gives you fix-by-fix instructions, including schema, robots.txt, llms.txt, and MCP snippets.
People don't want another dashboard. They want to know: 1. Can AI see my site? 2. Does AI mention my brand? 3. Which competitors get recommended instead? AIScan answers all 3 in one scan.
Semrush tells you rankings. AIScan tells you whether AI actually names your brand in answers. That gap is where the next wave of organic traffic is getting won or lost.
So I made the product brutally concrete. One scan. One visibility score. One brand mention report. One fix pack your dev can paste in. If the output isn't actionable, it's not an audit.
That's the annoying part nobody wants to admit. You can have a decent product and still lose because AI engines cite the wrong pages, ignore your schema, or trust competitors more. AIScan shows where you disappear.
AIScan runs 30 realistic prompts and measures your brand mention rate. Then it shows share of voice, competitor overlap, and the exact technical gaps blocking visibility. Basically: the report you wish Search Console had.
"Why isn't AI recommending us?" Usually it's not one thing. It's crawl access, weak schema, missing machine-readable docs, and no structured evidence for models to trust. AIScan maps the whole mess in minutes.
Angle: brand visibility and competitor mentions
Most SEO tools answer the wrong question. They tell you where you rank. They do not tell you whether AI answers name your brand at all. That matters now because people are asking ChatGPT, Perplexity, and Claude for recommendations before they click anything. We built AIScan to measure the part that matters: • Can AI see your site? • Can it cite your pages? • Does it recommend your brand over competitors? The Brand Visibility report runs 30 realistic prompts and shows mention rate, share of voice, and who gets recommended instead. This is the first time a lot of teams have had a concrete answer to: "Are we visible in AI search, or are we just hoping?" If you're in technical SEO or growth, I think this is going to become a standard audit soon.
Angle: developer-ready audit layer
The annoying thing about AI visibility is that everyone talks about it like philosophy. I wanted something operational. So AIScan does the boring part for you: • scans your site in about 60 seconds • runs 80+ checks • scores AEO, GEO, Agent Readiness, and MCP Readiness • returns fix-by-fix instructions • includes copy-paste snippets for schema, robots.txt, llms.txt, and MCP setup That means a marketer can use it as an audit. A developer can use it as a ticket. An agency can use it as a deliverable. AI engines do not browse like humans. They cite sources they already trust. If your site is hard to parse, hard to access, or hard to verify, you get skipped. We built AIScan to make that visible.
Angle: consultancy replacement and speed
A lot of companies are about to pay for AI visibility advice they could have gotten in one scan. That is why AIScan exists. It gives you the audit, the evidence, and the fix pack in minutes instead of a week of slides and calls. For a technical SEO lead, that means faster prioritization. For a founder, that means knowing what is blocking brand mentions. For an agency, that means a cleaner premium offer that clients can actually forward to engineering. The point is not to add another dashboard. The point is to answer a practical question: What do we need to change so AI engines can see, cite, and recommend us? If you are working on organic growth right now, this is probably the next audit layer you need.
Tagline
Audit AI visibility in 60 seconds
Description
AIScan scans your website for AI visibility, brand mentions, and machine-readable readiness. Get scores, competitor comparisons, and copy-paste fixes for schema, robots.txt, llms.txt, and MCP.
Maker's first comment
I built AIScan after watching teams pour time into SEO while AI answers started taking more of the first click. The frustrating part was how fuzzy the conversation was: people kept saying “AI search” like it was one thing, but in practice there are at least two problems - can models see your site technically, and do they actually mention your brand when users ask for recommendations? AIScan is my attempt to make that concrete. You drop in a URL, it scans the site, shows you where you’re blocked, and gives you the actual fixes instead of generic advice. I wanted something a technical SEO lead could use in a meeting, a founder could understand in five minutes, and a developer could turn into work tickets without rewriting the whole strategy. I’m launching this because I think AI visibility is becoming a standard part of organic growth, and I’d love feedback from people who are already dealing with it in the wild.
Pinned maker comment
Would love feedback on two things: whether the Brand Visibility report is clear enough for non-technical buyers, and whether the fix pack is specific enough for a developer to act on without extra guidance.
Meta
Targeting SaaS SEO leads who need proof AI sees them.
Hypothesis: technical SEO managers at SaaS companies will click if we show that AI visibility is measurable, not abstract. AIScan scans a site in 60 seconds, scores AI readiness, and shows which competitors AI recommends instead.
Google Search
Stop paying for audits that ignore AI answers.
Targeting founders and growth marketers searching for AI SEO audits. Hypothesis: when people need to know if ChatGPT and Perplexity can see, cite, and recommend their site, a fast audit with fix-by-fix output will beat generic SEO tools.
Reddit Promoted
I built a tool for the AI search problem.
Targeting indie founders, SEO consultants, and technical marketers who are already worried about ChatGPT/Perplexity traffic. Hypothesis: they want a concrete report on brand mentions and crawler readiness, not another big SEO platform.
Subreddits
r/SideProject
Show the problem, the scan output, and one before/after example of fixing AI visibility
Rules: No pure promo. Share what you built, what you learned, and include a useful screenshot or teardown.
r/indiehackers
Talk about building a new audit layer for AI search and invite feedback from founders shipping in public
Rules: Founder story first, product second. No spammy links without context.
r/microsaas
Share how AIScan can be used as a narrow, high-value audit product for SaaS teams and agencies
Rules: Focus on a specific micro-need and economics. Avoid broad marketing claims.
r/EntrepreneurRideAlong
Document the launch process and ask for reactions from founders dealing with flat organic traffic
Rules: Be transparent, educational, and avoid dropping a sales pitch in the opener.
r/SaaS
Discuss the shift from SEO rankings to AI recommendations and how teams can measure it
Rules: Must be practical, data-driven, and relevant to SaaS operators. Keep self-promo minimal.
Communities
Post build logs, ask for feedback on the category, and share one useful teardown per week instead of pushing the link every time.
Join revenue and growth discussions around AI search, then offer free mini-audits to people asking about traffic drops or brand visibility.
Share one crisp example of how AI visibility differs from traditional SEO metrics and invite marketers to compare notes.
Cold outreach template
Hey {firstName} - saw {context}. I’m building AIScan, which shows whether AI engines can see, cite, and recommend your site. If you want, I can run a free scan and send you the report.
Product Hunt timing
Launch on Tuesday at 10:00 AM Eastern Time. That hits North America and Europe while teams are active, and Tuesday tends to outperform Monday noise while still giving you enough weekday momentum for replies, shares, and follow-up demos.
Indie Hackers post ideas
- 01I built a scanner that tells you if AI can actually recommend your site
- 02What 30 AI prompts revealed about brand visibility across SaaS companies
- 03Shipping copy-paste fixes for schema, robots.txt, llms.txt, and MCP
Competitor alternatives
Current tone of voice
Provocative, developer-aware, and slightly rebellious. It uses lines like "Stop hiding from the future" and "AI engines don't browse. They cite sources they already trust."
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