Case study: in 2026, businesses in Murcia face a problem that traditional software does not solve: knowledge is distributed across documents, applications and people. An intranet with knowledge graph makes it possible to organize that knowledge and make it available to teams through AI. Q2BSTUDIO, a software development and technology company, has applied this architecture in a real case in Murcia, with measurable results that demonstrate the value of combining bespoke development, cloud integration and process automation. This article analyzes the case from a technical and business perspective.
The difference between a conventional intranet and an intranet with knowledge graph lies in semantics. The former stores pages and files; the latter represents concepts, relationships, people, projects and business rules. That network of connections allows an AI agent to answer questions with context, instead of returning unspecific links. For a company in Murcia with operations and back-office teams, the result is a faster way of working, with less duplication and better decision-making criteria.
The starting point was a mid-sized company with operations in Murcia, a little over twenty employees in operations and a mix of ERP, CRM, SharePoint and Teams. Each tool did its job, but knowledge did not travel between them. A commercial incident could be in the CRM, the logistics detail in the ERP and the relevant conversation in Teams. Without a thread connecting those data, management had no real visibility and teams lost hours on manual tasks. The intranet with knowledge graph was not designed as another portal, but as the layer that unifies information and gives context to current tools.
Q2BSTUDIO started with a discovery phase. This is not about installing a generic product; it is about understanding workflows, pain points and baseline metrics. During two weeks, the consulting team mapped processes, interviewed users and defined success indicators. That baseline makes it possible to measure the real impact of the solution, something that many companies do not do when implementing software. Thanks to that work, the project became a custom software development on a modular architecture, designed to grow with the business.
The next phase was building the knowledge layer. Instead of moving data to a new system, existing systems were connected through APIs and integration agents. The knowledge extracted from documents, records and conversations was normalized in the knowledge graph. To achieve this, Q2BSTUDIO combined language models with retrieval augmented generation techniques, so that AI answers rely on verifiable internal sources rather than hallucinations. This approach is especially relevant in Murcia, where many companies want useful AI without replacing the investments they have already made in ERP or CRM.
One of the most valued elements was the introduction of AI agents inside the intranet. These agents are not simple chatbots; they execute tasks, query the knowledge graph and update records with human supervision. For example, an agent can classify an email, locate the related project, prepare a response and propose a next step. In critical processes, a human control point was maintained, which reduces risk and builds confidence in adoption. The integration of AI agents with custom software made it possible to adapt each rule to the company's real operation, something that cannot be achieved with closed tools.
The technological infrastructure was based on AWS/Azure cloud. The company needed AI services to connect securely with on-premises systems. Q2BSTUDIO designed a private network through VPN and private endpoints, so data never traveled over the public internet. Cybersecurity was a requirement from the beginning: role-based authentication, access auditing, encryption in transit and at rest, and GDPR alignment. Those responsible for the project knew that an intranet with knowledge graph is only useful if protected information remains protected.
A reporting and observability layer for management was also added. Usage metrics, process times and the quality of AI answers were loaded into a dashboard with BI/Power BI. This allowed middle managers to make data-driven decisions and justify the investment to the finance department. In a mid-sized company, visibility is often one of the biggest benefits, because it reduces noise and helps identify bottlenecks. The information from the knowledge graph thus became a source of business intelligence, not just an internal search engine.
During the controlled rollout phase, Q2BSTUDIO's team worked with the client in Murcia to validate the solution with a small group of users before expanding it. This strategy made it possible to adjust flows, correct exceptions and train key people. Process automation was applied gradually: first low-risk, high-volume tasks, then more complex operations. As a result, the team trusted the system and errors were not propagated. A phased deployment reduces friction and accelerates internal adoption.
After three months, the results showed a clear reduction in manual tasks and an acceleration of work cycles. The organization moved from relying on spreadsheets and email approvals to operating with an intranet that knows the relationship between each element. Onboarding time for new people also improved, because new employees can ask the AI and get answers with context. This is not a cosmetic effect: it reduces operating costs, improves quality and frees up capacity for higher-value tasks.
From a technical point of view, the project shows that a knowledge architecture does not require replacing all systems. The key is to normalize data and define the relationships that matter. Q2BSTUDIO applied agile development methodologies, with deliveries every two weeks and priority reviews with the client. Business knowledge was incorporated into the graph incrementally, which facilitated change management. The lessons learned in this case study in Murcia align with a reality seen in many projects: technology is necessary, but human factors and process design are what determine ROI.
For executives evaluating an intranet with knowledge graph solution, Q2BSTUDIO's recommendation is clear: first define the business problem, then measure the improvement, and choose a technology partner that combines custom applications, cloud, cybersecurity, BI/Power BI and AI agents. In Murcia, the company has demonstrated the ability to offer all of that in a single project, with local teams and close support. This case is not a promise for the future, but a reality implemented in 2026.
If your business wants to replicate this approach, it is useful to start with a diagnostic session with Q2BSTUDIO. It assesses the starting point, critical flows and automation opportunities. There is no need to change ERP, CRM or collaboration platform. What is needed is to organize knowledge so that an intranet with knowledge graph can provide answers, automation and visibility. The next step is turning that technological advantage into a real competitive advantage in the Murcia market.
