GEO for a clearer representation of your brand in AI answers
Assess how AI answers represent your brand. Improve entity clarity, verifiable information and monitoring without promises of mentions or recommendations.

Representation, omissions and errors
When someone asks an AI system about a solution, the answer may combine information from several sources. Your brand might be missing, described incompletely or associated with services you no longer offer. A single observation cannot establish what every potential customer will see, but it can reveal questions worth investigating in a more structured way.
Questions worth observing
Grupo Diasan’s GEO service reviews that representation and proposes improvements to the clarity of published information. We start by agreeing which queries matter to the business, which languages to assess and which systems and conditions to document. Brand-specific questions are distinguished from category questions: an accurate description is not the same as a commercial recommendation.
Entities and verifiable sources
We then examine organizational identity, relationships between services and consistency across relevant pages and profiles. Recommendations may cover verifiable content, appropriate authorship information, relevant references and ambiguous descriptions. We also review technical access and structured data that reflects visible information. JSON-LD can help describe entities, but it cannot require a system to cite a source.
An information inventory with review owners
Remote collaboration is organized around an information inventory, priorities and validation. Content and deliverables can be prepared in Spanish, English or both, depending on scope and budget. Where a recommendation needs industry, legal or product review, we agree who can confirm the information before publication.
A hypothetical conflicting-source scenario
Imagine a business whose website describes a current service while an older profile describes a discontinued offer. The work would involve finding contradictions, correcting sources within its control and observing subsequent answers through a documented query set. This scenario illustrates the method; it is not evidence of a client result.
Comparable records and limitations
Monitoring records dates, context, answers and cited sources where available. Model changes, personalization and response variability prevent these observations from becoming a universal measure of market visibility. We do not promise mentions, recommendations or a timetable for updates. GEO shares foundations with SEO, but this service focuses on understanding and representation in AI answers. Tell us which questions matter to your business so we can assess whether a focused diagnostic project would be useful and what evidence it could reasonably collect.
Questions and next step
Frequently asked questions03
Can an inaccurate answer be corrected directly?
We can correct owned information and request changes to external sources where a process exists. We do not control answers or guarantee when they will reflect an update.
Do we need llms.txt to appear?
It is not a universal requirement or a guarantee that systems will use it. It would only be considered as an experimental resource, not a substitute for accessible content, verifiable information or appropriate technical controls.
How do you avoid treating a test as a trend?
We document queries, language, date, system and available conditions, repeat observations and explain limitations. A single screenshot is not generalized to the whole audience.