Reach. Understand. Trust. The Swedish platform turns verifiable website checks into clear reports agencies can present, defend and turn into client action.
AEOmotor has launched a rule-based website analysis engine built specifically for digital and marketing agencies that need to explain how well their clients’ websites are prepared for AI systems.
AEOmotor helps agencies produce website analyses they can understand, present and defend in front of their clients. Instead of asking a large language model to interpret a website and determine the findings, the engine applies defined rules to observable conditions across the actual website.
The analysis is structured around three questions:
Reach. Can AI systems access and extract the website’s content?
Understand. Can they understand the business, its offering and how the information is structured?
Trust. Can they identify the trust signals needed to treat the information as credible and usable?
Each finding is connected to traceable evidence, a clear explanation of why it matters and a prioritized action. The result is technically rigorous enough for specialists while remaining understandable for non-technical clients and decision-makers.
“Agencies do not need another polished report that becomes difficult to explain when the client asks why,” said Amir Chamsine, founder and CEO of AEOmotor. “They need to show what was found, what the conclusion is based on and what should happen next. The report is the output. The analysis engine is the product.”
Website analysis in minutes
AEOmotor analyses each website based on its actual content, structure and technical conditions. A typical analysis takes between one and three minutes, depending on the number of pages, the size of the website and how resource-intensive it is to process. Websites with fewer than approximately 50 pages can often be analysed in under a minute.
This allows agencies to examine multiple clients and prospects without turning every initial analysis into a lengthy manual audit. The engine provides a consistent analytical foundation, while the agency applies its customer knowledge, strategy and implementation expertise.
The analysis does not promise that a company will be mentioned or cited in a particular AI-generated answer. It examines the underlying conditions that can influence whether AI systems are able to access, understand and use the company’s information.
From finding a problem to creating client value
AEOmotor is designed to support the full agency workflow rather than stop at report generation.
Agencies can use the analysis to identify relevant prospects, open new client conversations, support proposals and create a clear plan for implementation. The findings can then lead to concrete work within the services the agency already provides, followed by recurring measurement and verification.
The report is designed to make this process understandable for everyone involved. It shows the client what was found, why it matters, what should be prioritized and who should take responsibility for the next step.
Two delivery models for agencies
Agencies that already have the necessary internal competence can use AEOmotor independently across multiple clients. They receive access to the analysis engine and scalable report volumes for prospecting, full client analyses and recurring follow-up. Co-branded and white-label delivery options allow the agency to integrate the methodology into its own customer offering.
Agencies that are still building their competence can begin with specialist-led delivery. In this model, AEOmotor leads the analysis, interpretation, prioritization and client walkthrough. The agency retains the customer relationship, commercial responsibility and implementation work.
Both models use the same rule-based engine and the same Reach, Understand and Trust framework. The difference is who leads the delivery.
Measuring both what happens and why
Alongside the website analysis, AEOmotor measures how companies appear in AI-generated answers, including Share of Answers and Share of Voice.
These two layers are kept methodologically separate. AI-generated answers are probabilistic and can change between observations. The website analysis uses repeatable, rule-based checks that can be traced back to observable evidence.
This gives agencies a clearer way to connect what is being observed in AI-generated answers with website conditions that may help explain it. Agencies can then prioritize improvements and follow whether the observed results change over time.
“Monitoring can show an agency what happened,” Chamsine said. “AEOmotor is built to also help establish why, decide what to do next and verify the work afterwards.”
