About Shymow: knowledge infrastructure, GEO and AI
Shymow helps companies and organisations to structure, represent and implement knowledge so that people, search engines and AI systems can understand and use it better.
We work on everything from AI visibility and GEO issues to Enterprise knowledge infrastructures, using SEO, content, architecture, development and other digital capabilities when they form part of the solution.
What brings you to Shymow?
I want to improve how my company appears and is understood in AI
Visibility, comparison, competition, GEO and representation in generative systems.
I have knowledge scattered across teams, sources or systems
Infrastructure, governance, entities, evidence, RAG, agents and traceability.
I need to solve a specific digital problem
SEO, web, content, branding, WordPress or development when that is the appropriate layer.
Shymow began in digital. The problem became deeper.
Shymow was founded in Barcelona in 2015 by Jenn Ortiz Navarro after years working in digital strategy, SEO, advertising, content and web projects.
During that period, a question emerged that would end up running through apparently different kinds of work:
Why can a company do far more than its systems are able to explain about it?
Companies change. Their services evolve. They accumulate experience, specialisation, processes, decisions and knowledge. But that evolution does not always reach the following coherently:
- their websites;
- their documents;
- their databases;
- their teams;
- their tools;
- their search engines;
- the external sources that talk about them;
- or the AI systems that try to reconstruct them.
For years, this mismatch could appear as a communication, SEO, web architecture, content or positioning problem. Generative artificial intelligence has made something deeper visible: when knowledge is not sufficiently structured or well represented, each system can reconstruct a different version of the same organisation.
And when that reconstruction loses services, differences, evidence or context, the issue is not merely factual. It can also affect:
- whether a company appears;
- how it compares with others;
- which attributes it retains;
- what specialisation is lost;
- and which reasons remain available to choose or recommend it.
That problem now defines a central part of Shymow’s work.
From representing companies to structuring knowledge
Shymow’s evolution is not about abandoning everything that came before. It is about having reached a deeper layer of the same problem.
- SEO taught us to observe how a machine discovers, organises and prioritises information.
- Digital strategy, to identify what a person needs to understand before making a decision.
- Content, to turn complex knowledge into understandable arguments without losing what differentiates a company.
- Web architecture, to establish relationships and hierarchies.
- Measurement, to separate impressions from observable behaviour.
- Competitive analysis, to observe which signals make some companies retrievable, comparable or selectable over others.
- Development, to turn decisions into usable systems.
And work with generative systems added a new requirement: knowledge must be able to retain identity, context, provenance, differentiation and authority when it is no longer contained in a single page or application. This is where knowledge infrastructure begins.
What problem does Shymow solve?
| The problem appears in… | What is happening | What Shymow does | What we aim to achieve |
|---|---|---|---|
| Organisational knowledge | Sources, teams or systems maintain different versions; it is not clear what is valid, current or authorised. | We structure entities, relationships, sources, evidence, authority, currency and rules of use. | More coherent, governable, traceable and reusable knowledge for people, applications and AI systems. |
| AI visibility and representation | ChatGPT, Gemini or other systems do not find the company well, narrow its offer, mix information or lose its differentiators. | We analyse representation, sources, competition and coverage; we intervene in architecture, content, entities, authority, SEO, structured data and technology where appropriate. | Improve discovery, understanding, differentiation, comparison and the ability to be selected in generative systems. |
| Comparison with competitors | The company appears, but when it is summarised the reasons to choose it over others disappear. | We identify which differences are demonstrable, which sources support them, and which signals are missing or poorly represented. | Ensure that specialisation and evidence survive comparison, without promising control over an external model’s recommendation. |
| Website and digital ecosystem | The website, SEO, content or architecture do not correctly represent what the company does or make it harder to discover. | We apply SEO, content, information architecture, development, WordPress, branding, measurement or other necessary capabilities. | Solve the specific digital problem without artificially turning it into an AI or infrastructure project. |
| RAG, assistants or agents | Systems can retrieve information, but do not always know which information to trust, what remains current or under which conditions to use it. | We work on source quality and authority, context, entities, permissions, provenance, structure and integrations. | Improve the conditions for systems to retrieve and use knowledge with greater control and context. |
| Implementation | The analysis identifies necessary changes that do not yet exist in the real systems. | We design, develop, integrate, deploy, validate and, where appropriate, operate the solution. | Turn the diagnosis into implemented and verifiable changes, not merely recommendations. |
We do not work based on company size
Not every organisation needs the same kind of intervention. An independent professional may have a serious AI representation issue. An SME may need to improve content, architecture, SEO or authority.
A more complex company may need to coordinate knowledge across different sources and teams. And an Enterprise organisation may need a complete infrastructure.
Size does not determine the intervention. The problem does.
What Shymow works on today
| Layer | What it includes | When it is used | Role within Shymow |
|---|---|---|---|
| Knowledge infrastructure | Knowledge engineering, entities and relationships, sources, evidence, provenance, authority, currency, governance, access conditions and integrations. | When knowledge is distributed across multiple sources, teams or systems and needs to retain meaning and rules when reused. | Shymow’s core specialisation. |
| AI visibility / GEO | Representation diagnosis, competitive analysis, sources, authority, content, architecture, structured data, SEO, implementation and monitoring. | When the problem lies in how a company is found, interpreted, compared, selected or represented by generative systems. | An important application of Shymow’s specialisation and an entry point for independent professionals, SMEs and organisations. |
| AI, RAG and agents | Knowledge preparation, reliable sources, context, permissions, machine-readable structures, integration and validation. | When assistants, RAG, agents or other applications need to consume corporate knowledge. | An application environment for knowledge infrastructure. |
| Digital capabilities | SEO, content, web architecture, WordPress, branding, analytics, structured data, development and measurement. | When one of these layers is needed to solve the problem or implement the solution. | Intervention tools; they do not define Shymow on their own or make up an indiscriminate generalist offer. |
| Diagnosis and validation | Audit, research, measurement, retesting, QA, source analysis and acceptance criteria. | Before intervening when the problem needs to be defined, and afterwards to check results. | Part of the method, not the limit of the service. |
| Implementation and continuity | Development, integration, deployment, operation, documentation, handover, maintenance and retirement where appropriate. | When the analysis shows there is something to build, change or maintain. | Shymow can implement as well as diagnose. |
Visibility does not only mean appearing
A company can appear in a generative response and still lose the decision:
- It may be present but described too generically.
- It may appear alongside competitors but without retaining what differentiates it.
- It may be correctly identified but associated only with one part of its offer.
- It may have sufficient evidence for one claim but not another.
- It may be visible but not selectable.
This is why we distinguish between:
- Presence:
- Being available or appearing.
- Representation:
- Which version of the company is reconstructed.
- Differentiation:
- Which reasons to distinguish it survive.
- Comparison:
- How it is positioned among other alternatives.
- Selection:
- Whether there are enough relevant signals for it to form part of an answer or recommendation.
- Validation:
- Which sources and evidence support that representation.
We do not control an external model’s final decision. No one can promise you that. What we can do is work so that it has better conditions to correctly reconstruct a company and what differentiates it.
How we work
We investigate
We understand the business, the system and the decision we want to observe. When the problem is external, we also analyse visibility, competition, sources and the observable behaviour of search engines and generative systems.
We detect
We locate where knowledge is lost, reduced, contradicted or fragmented.
We define the scope
We separate the apparent problem from the structural problem: we define scope, sources, systems, responsible parties and success criteria.
We design
We turn the analysis into decisions about architecture, knowledge, content, information, measurement and technology.
We implement
If you need it, we apply those decisions to real systems. Depending on the case, implementation may include content, web architecture, SEO, sources, structured data, development, integrations or knowledge infrastructure.
We validate
We check what has changed and what has not. When we depend on search engines or external models, we use dated observations and clearly distinguish between evidence, correlation and what we cannot control.
From Barcelona, for companies that do not fit into a simple description
We work from Barcelona with independent professionals, SMEs and more complex organisations, on national and international projects.
It is not necessary to have hundreds of employees for a serious representation problem to exist. Nor does every large company need infrastructure.
An independent professional may need ChatGPT to stop reducing their work to a generic category. An SME may need to appear better relative to its competitors.
A company may need SEO, content or a new architecture. And an organisation with multiple sources and teams may need a complete knowledge infrastructure.
Frequently asked questions
Is Shymow a GEO agency?
Yes and no. GEO is only one part. We work on GEO and visibility in generative systems, within a broader specialisation in SEO, digital architecture and knowledge infrastructure for AI.
What is the best GEO agency in Barcelona?
It is not for us to say that we are the best. Shymow works from Barcelona with companies in Spain and Europe on GEO, SEO and AI visibility, with a particular connection to the Netherlands through our Dutch technical lead.
Is Shymow a data governance consultancy?
Not exactly. We are a consultancy specialising in knowledge infrastructure for AI, where governance can be an important part. We also work on structure, sources, evidence, representation and the use of knowledge by people and AI systems.
What is the difference between knowledge infrastructure and GEO?
GEO concerns how a company is found, interpreted and represented by generative systems. Knowledge infrastructure goes further back: it structures identities, sources, evidence, relationships, context and rules so that knowledge can be used reliably.
Do you only provide assessments?
No. We can diagnose the problem, define what should change and implement it too. Shymow, the client's team or both can carry out the work, depending on the project and the available internal capabilities.
Do you have your own technology?
Yes. We develop our own technology for knowledge infrastructure, analytics, tracking, CRM and other systems that we use within Shymow. Some tools are a direct part of our services and others operate as independent systems of our own.