Intranet with knowledge graph in Santa Cruz de Tenerife: Q&A 2026
When a company in Santa Cruz de Tenerife decides to modernize its intranet, it is not just looking for a better search engine. It is looking for a way to connect internal knowledge with decisions, processes and people. An intranet with knowledge graph delivers that connection: it turns documents, data and experiences into a living map that artificial intelligence can navigate to provide useful answers.
Q2BSTUDIO is a software development and technology company that designs this kind of solution. Its approach combines custom software development, artificial intelligence, cybersecurity and AWS/Azure cloud services. It does not sell a closed tool; it builds a platform adapted to each organization's reality, with the ability to evolve.
This article answers, in a question-and-answer format, the main concerns of management and technical teams before undertaking an intranet with knowledge graph project. The goal is to provide a clear and practical view for 2026.
Organizations operating in Tenerife work with heterogeneous systems: ERPs, CRMs, spreadsheets, SharePoint, Teams and proprietary tools. Knowledge is duplicated, lost or blocked in isolated departments. A knowledge graph makes it possible to relate information from all those systems without having to migrate them all to a single platform.
Unlike a traditional keyword search, the graph understands entities and relationships. For example, it not only finds a document that mentions an invoice, but also knows which customer, project and payment date are associated with that invoice. That level of context is what enables AI agents to act with precision.
1. What exactly is an intranet with knowledge graph? It is an internal platform that structures knowledge as a graph of entities and relationships: people, projects, documents, customers, processes and systems. Each element is linked to others according to context, and that semantic network is used to deliver intelligent search, recommendations and automation.
2. What problems does it solve for a company in Tenerife? It reduces time wasted looking for information, speeds up employee onboarding, helps find internal experts and connects teams working on different islands or remotely. It also frees teams from repetitive tasks, because automated workflows rely on corporate knowledge.
3. Can it integrate with systems we already use? Yes. Integration is done through APIs, connectors and enterprise services that extend SAP, Salesforce, Odoo, SharePoint, Microsoft Teams and other tools. The intranet becomes a knowledge layer that leverages existing investment and does not force replacement of critical systems.
4. What role does AI play in this type of intranet? AI makes it possible to search and generate answers from corporate documents using RAG, language models and vector databases. In addition, AI agents can execute actions, update records, prepare reports and notify managers about incidents.
5. What services does an intranet with knowledge graph project include? It usually includes upfront discovery, data architecture design, custom software development, integration with existing systems, AI configuration, security, dashboards and training for internal teams.
6. How long does it take to see results? Discovery usually takes one or two weeks. With that information, a first viable product (MVP) is built in four to eight weeks. A full deployment, with integrations and advanced workflows, can be completed in two to four months.
7. How is return on investment measured? Before starting, KPIs are defined based on operations: cycle times, manual errors, cost per process, employee satisfaction and adoption. After launch, Business Intelligence and Power BI dashboards show progress from the initial situation.
8. What level of security can be expected? A responsible implementation includes role-based access control, audit trails, encryption in transit and at rest, and remote access protocols using VPN. If AI services handle sensitive data, private endpoints and isolated cloud environments are configured.
9. How do you decide between AWS and Azure? Q2BSTUDIO proposes a neutral architecture. When the company already uses Microsoft, Azure simplifies integration with Active Directory, Power BI and SharePoint. AWS has a broad catalog of data and AI services. The decision is made according to data, budget and industry compliance requirements.
10. Why choose Q2BSTUDIO for this project? Because it is a team specialized in custom software and enterprise artificial intelligence, able to work agilely on critical projects. At the end of each project, the client receives source code, documentation and a management platform that lets them operate the AI autonomously.
The cost of an intranet with knowledge graph depends on scope and level of integration. A focused project can range from 5,000 to 60,000 euros, with payback periods usually under one year. More important than the initial budget is understanding that this investment is not limited to a tool: it is aimed at reducing manual work and errors in specific processes.
Q2BSTUDIO also develops a web portal so the client can manage its own AI agents, review costs, adjust instructions and measure automation performance. This autonomy is key to ensuring the solution does not depend on external consulting in daily operations.
Cybersecurity is not a final stage. During discovery, risks, data classification and access rules are identified. In regulated environments, human validation and audit trails ensure traceability. Cybersecurity is embedded in the architecture, not added at the end.
In 2026 the competitive edge is no longer about having data, but about knowing how to activate it. Companies that make it possible for employees to find the right knowledge at the right time make better decisions. The combination of knowledge graph, generative AI and automation is the natural way to achieve this in Santa Cruz de Tenerife.
An intranet with knowledge graph is a strategic investment, not a cosmetic project. To achieve real results, it takes a company that understands both custom software and integration, security and AI. Q2BSTUDIO brings that experience with a practical, close-to-the-client approach focused on ensuring the client retains control of its technology.
