AIRANKS is an AI visibility measurement and ranking platform designed to show how brands, websites and individual web pages appear inside answers generated by artificial intelligence models.
Traditional SEO tools mainly measure visibility in search engines. AIRANKS takes a different approach by measuring visibility within AI generated answers. It asks AI models real product and service related questions, records their responses and analyzes which brands are mentioned, which domains are cited and which specific pages receive links.
The platform turns these observations into searchable rankings for phrases, brands and domains. Each qualifying domain receives an AIR score from 1 to 10, representing its relative visibility within the active AIRANKS dataset.
AIRANKS also provides domain reports that help website owners understand how AI systems see their sites. Reports can show AI citations, a machine generated summary and technical signals such as llms.txt availability, robots.txt permissions for AI crawlers, JSON-LD and sitemap status.
The platform is particularly relevant for SEO professionals, marketers, publishers, brands and website owners who want to understand visibility beyond Google and traditional search engines as AI assistants increasingly influence how people discover products and information.
Features
AIR Score
AIRANKS assigns qualifying domains an AIR score from 1 to 10.
The score represents a visibility decile based on how often the domain appears within the AI responses contained in the active dataset.
A score of 7, for example, means that the domain falls within the seventh visibility band. It does not mean the website received 70 points out of 100.
A score of 0 represents insufficient data rather than poor performance.
AI Visibility Measurement
AIRANKS measures whether brands and domains actually appear in AI generated answers.
Instead of estimating visibility from conventional SEO metrics, the platform records responses generated by AI models and derives its rankings from those observations.
Live AI Rankings
The platform provides a live ledger covering:
Phrases
Brands
Domains
Users can explore what AI models say when asked particular product and service related questions and see which brands and websites appear most frequently.
Phrase Rankings
Users can search for specific questions or phrases and examine which brands appear in AI responses.
This can help marketers understand how AI models respond to recommendation style queries relevant to their industry.
Brand Visibility
AIRANKS tracks brands mentioned within AI generated answers.
This provides another way to evaluate brand awareness beyond website traffic and conventional search rankings.
Domain Citation Tracking
The platform records which domains AI models cite when producing answers.
This can help publishers and businesses understand whether their websites are being used as sources within AI responses.
Page Level Citation Tracking
AIRANKS goes beyond domain level visibility by recording the exact web pages linked within captured AI responses.
This can help website owners identify which articles, product pages, guides or other resources are receiving AI citations.
Domain Reports
Users can generate reports for individual domains.
These reports provide an AIR score along with additional information about how AI systems currently understand and reference the website.
Machine Summary
Domain reports include a machine generated summary describing what the AI understands about the website.
This can help businesses see whether their brand, products or services are being interpreted correctly.
AI File Audit
AIRANKS checks technical signals that may affect how AI systems access and understand a website.
The audit covers elements such as:
llms.txt
robots.txt
AI crawler permissions
JSON-LD structured data
Sitemap availability
AI Crawler Checks
The platform examines robots.txt rules for AI related crawlers including GPTBot, OAI-SearchBot, ClaudeBot and PerplexityBot.
Website owners can use this information to understand whether their current configuration permits or restricts particular AI crawlers.
Confidence Intervals
AIRANKS recognizes that AI model responses can vary even when the same question is asked repeatedly.
Instead of presenting every ranking as an absolute fact, the platform provides confidence information where sufficient observations are available.
Rank Stability
AIRANKS uses repeated sampling to calculate how stable a particular ranking is.
For each phrase, collected observations are resampled 1,000 times. The platform then measures how frequently a brand maintains the same position.
This helps users distinguish between relatively stable rankings and positions that change frequently.
Repeated AI Queries
AIRANKS does not base a ranking on a single AI response.
Its published methodology states that each question is sent through 100 separate model runs split across two models. This creates a larger distribution of responses from which rankings can be calculated.
Transparent Methodology
The platform publicly explains how its ranking methodology works, including repetition, ranking position, confidence calculations, AIR scores and minimum data thresholds.
It also openly describes limitations in what its measurements can establish.
AIR Toolbar
AIRANKS offers a free browser extension called AIR Toolbar.
The extension can display information about the website currently open in the browser, including its AIR score, AI file audit, crawler permissions and machine generated site summary.
Public API
AIRANKS provides a public read API covering domains, brands, phrases and search.
This allows developers and organizations to integrate AIRANKS data into their own applications, dashboards or research workflows.
llms.txt Resources
AIRANKS supports and audits llms.txt and related AI oriented website files.
It also publishes its own llms.txt, llms-full.txt and ai.txt resources.
How It Works
Step 1: AIRANKS asks AI models questions
The system uses real product and service related queries rather than relying only on traditional search engine information.
Step 2: Questions are repeated
Each phrase is run multiple times across AI models to account for the natural variation in generated answers.
Step 3: Complete responses are recorded
AIRANKS stores the generated answer as an observation, including the question, brands mentioned and websites or pages cited.
Step 4: Brand mentions are analyzed
The platform identifies which known brands appear within each response and their first position in the answer.
Step 5: Citations are recorded
Domains and exact web pages cited by the AI are captured.
Step 6: Rankings are calculated
AIRANKS uses the accumulated observations to produce phrase, brand and domain rankings.
Step 7: AIR scores are assigned
Domains with sufficient observations receive an AIR visibility score from 1 to 10.
Step 8: Stability is measured
For qualifying phrase rankings, AIRANKS performs 1,000 resamples to estimate confidence and ranking stability.
Step 9: Users analyze their domains
Website owners can open a domain report to examine AI visibility, cited pages, technical AI files and how the site is understood by AI systems.
Use Cases
SEO Professionals
SEO specialists can add AI visibility monitoring to traditional search engine optimization workflows and investigate whether clients appear in AI generated recommendations.
Brands
Companies can monitor whether their brands are mentioned when AI systems answer relevant product and service questions.
Digital Marketers
Marketing teams can compare AI visibility across brands and identify areas where competitors may be appearing more frequently.
Publishers
Content publishers can identify which domains and individual pages receive citations from AI generated answers.
Website Owners
Website owners can use domain reports to understand their AIR score and check technical elements such as llms.txt, structured data, sitemaps and AI crawler access.
Content Teams
Content teams can study which types of pages receive AI citations and use those insights when planning future content.
GEO and AEO Professionals
Professionals working in Generative Engine Optimization and Answer Engine Optimization can use AIRANKS as a measurement source for understanding visibility within AI responses.
Competitive Research
Businesses can compare how frequently their brands and competitors appear for commercially relevant questions.
Developers
Developers can access AIRANKS data through its public API and incorporate domain, brand and phrase information into other applications.
AI Visibility Audits
Agencies can use domain reports and AI file audits when assessing whether a client’s website is technically prepared for AI discovery.
Pricing
AIRANKS is currently free until further notice.
The official website states that there are currently:
No paywalls
No subscription gates
No seat based checkout fees
Domain reports, rankings, methodology information, the live ledger and public API are currently available free of charge.
Because the website specifically describes this arrangement as free until further notice, users should be aware that pricing or access conditions could change in the future.
Strengths
AIRANKS focuses specifically on AI visibility rather than attempting to treat traditional Google rankings as a substitute for visibility within AI generated answers.
Its methodology is publicly explained, making it easier for users to understand how rankings are produced.
The platform repeatedly asks the same question rather than treating one AI response as representative of how a model will always answer.
Confidence intervals and stability measurements provide useful context because generative AI responses naturally vary.
AIR scores provide a relatively simple way to understand a domain’s position within the active dataset.
Page level citation tracking can help publishers understand which individual pieces of content AI systems are referencing.
Domain reports combine visibility information with technical AI readiness checks such as llms.txt and AI crawler permissions.
The free browser toolbar makes it easier to inspect websites while browsing.
A public API gives developers and agencies the option to work with AIRANKS data programmatically.
Drawbacks
AIRANKS measures a defined sample of AI model responses rather than every interaction taking place across consumer AI platforms.
Its own methodology makes clear that API model responses may differ from consumer chatbot experiences, particularly when consumer applications perform live web searches.
The platform currently samples a limited number of AI models, so an AIR score should not be interpreted as universal visibility across every generative AI system.
AI responses can vary considerably, which is why rankings need confidence and stability measurements in the first place.
Brand detection also depends on AIRANKS knowing the relevant brand and its aliases. New, obscure or unusually named brands may therefore be harder to identify correctly.
The active dataset determines the AIR score, so the metric should be interpreted within the context of AIRANKS’ dataset rather than as an absolute industry wide measurement.
The platform is also relatively specialized. Businesses looking for conventional keyword rankings, backlinks, technical SEO crawling and broader search analytics would still need traditional SEO tools.
Comparison with Other Platforms
AIRANKS belongs to the growing category of AI visibility and Generative Engine Optimization measurement tools.
Traditional SEO platforms generally focus on Google rankings, keywords, backlinks, search traffic and technical website performance. AIRANKS instead asks a different question: how visible is a brand or website when AI models generate answers?
Another notable difference is its emphasis on measurement transparency. AIRANKS publishes details about repeated model runs, resampling, stability and confidence rather than presenting AI visibility as a completely deterministic metric.
The AIR score also differs from traditional SEO authority scores. It is based on observed visibility within the platform’s active AI dataset rather than backlink authority or conventional search ranking factors.
AIRANKS should therefore be viewed as complementary to traditional SEO software rather than a replacement for it. Search engine visibility and AI visibility are related areas, but they measure different discovery environments.
Customer Reviews and Testimonials
Customer reviews and testimonials are not clearly available on the official website.
AIRANKS primarily provides its methodology, live dataset, reports and technical documentation rather than relying heavily on customer testimonials to explain the platform.
Conclusion
AIRANKS is a specialized analytics platform for understanding how brands and websites appear inside AI generated answers.
It tracks three particularly useful signals: which brands AI models mention, which domains they cite and which individual pages they link to. It then organizes these observations into searchable rankings and a 1 to 10 AIR visibility score.
The platform may be especially useful for SEO professionals, GEO specialists, content marketers, publishers, agencies and businesses that want to understand how the shift toward AI based discovery is affecting their visibility.
Its transparent methodology is a notable strength. Repeated queries, confidence intervals and rank stability measurements acknowledge that AI responses are variable rather than pretending that one chatbot answer represents a permanent ranking.
AIRANKS does not replace traditional SEO analytics, and its results should be understood within the limits of the models and dataset it measures. However, as a complementary tool for tracking brand mentions, AI citations and website visibility in generative answers, it offers a useful perspective that conventional search ranking tools may not provide.
The fact that its rankings, domain reports, live ledger and public API are currently free also makes AIRANKS easy for website owners and marketers to explore before deciding how AI visibility should fit into their broader SEO and content strategy.
