AEOmotor is an AEO infrastructure for organizations that want to understand and improve their visibility in AI-generated answers.
No scores. Just observable signals you can act on.
2025 marked a clear shift where AI-based search and AI-generated answers went from experiment to strategic focus for the largest players.
This changes how visibility works. This is the environment AEOmotor is built for.
AEOmotor is an AEO infrastructure and SaaS platform for organizations that need to understand how AI systems select, summarize and cite content.
The platform is developed for environments where answers are generated, not ranked. AI systems use no scores or positions. Therefore, neither does AEOmotor.
You enter your domain, brand, industry and any competitors. The system crawls your core pages and analyzes structural signals that AI systems use to understand and cite content.
This includes structured data according to Schema.org, content structure and hierarchy, entity structure and technical prerequisites.
The analysis is deterministic and rule-based. No AI guesswork.
The system identifies search queries where you should be visible but are not. Each gap is classified as:
Gaps that can be addressed are prioritized based on actual impact.
For identified issues, the system generates ready-to-use Schema.org fixes that can be implemented directly on the website.
Everything is deterministic and based on your actual data. No AI-generated suggestions.
Everything is collected in a dashboard where you can see the status of all factors, add keywords for monitoring, implement actions and follow how your mentions develop over time.
The platform is built for continuous work, not one-time analysis.
Elmer is a built-in guide that helps you understand the analysis and prioritize the right actions. He explains why something is missing, helps you interpret content gaps and answers questions about where to start.
Elmer always bases his guidance on your actual data and the analysis the system has already performed.
After implementing changes, you follow how AI mentions, citations and sources change over time. This makes it possible to see long-term patterns, not just individual changes.
Classic SEO tools measure rankings, backlinks and domain authority. AEOmotor measures how AI systems select, summarize and cite information.
AI-generated answers have no positions. Therefore, we show mentions, citation frequency and competitor presence – observable signals that actually affect visibility.
Where possible, we use rule-based analysis instead of AI guesswork. Schema validation, structure checks and fix generation are 100% deterministic.
Raw data is separated from analysis and presentation. You can export, integrate and verify without being locked into our interpretation.
Data separation and privacy protection are built in from the start, not added as an afterthought.
For small and medium-sized companies that want to monitor their AI visibility.
SEK 1,990 per month
For organizations that want to handle AEO in-house and measure development over time.
Everything in Starter plus:
SEK 4,990 per month
For SEO agencies and marketing teams that want to offer AEO analysis to their clients.
Contact us for quote
AEOmotor is built and operated in Microsoft Azure with data located in Sweden through Azure Sweden Central. All processing takes place within the EU and is adapted for organizations with high requirements for data protection and regulatory compliance.
GDPR and data separation are architecture principles from the start.
SEO optimizes for positions in traditional search results where rankings, backlinks and domain authority determine visibility. AEO optimizes for AI-generated answers where there are no positions – just the choice to cite or not cite. AI systems like ChatGPT and Perplexity value structured data, clear answers and semantic correctness rather than link profiles. Both disciplines are needed, but they measure different things.
AI-generated answers work fundamentally differently than traditional search. There are no positions 1-10, just one answer compiled from multiple sources. A calculated AEO score would be arbitrary and have no connection to how AI systems actually work. Instead, observable signals are more relevant: whether you are mentioned or not, which competitors are cited, and how this changes over time.
The effect is measured by tracking mentions and citations in AI systems over time. When you implement Schema.org markup or improve content structure, you can observe whether citation frequency changes at the next monitoring. Long-term trends show patterns that individual data points cannot capture. History over 60-365 days provides a basis for assessing actual impact.
The five largest AI systems that generate answers based on web content are Perplexity, Google Gemini, OpenAI ChatGPT with web search, Google AI Overviews (integrated into Google Search) and Microsoft Copilot via Bing. These systems have different model behaviors and may cite different sources for the same question. Monitoring multiple AI engines gives a more complete picture of your visibility.
Deterministic analysis means that schema validation, structure checks and fix generation are done with fixed rules instead of AI guesswork. This ensures reproducible and verifiable results. Monitoring collects actual AI-generated answers from various AI engines and analyzes them systematically. Separation between raw data, analysis and presentation makes it possible to export and verify results independently.
No hype. No scores. Just observable signals you can act on.
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