Calculating the cost of an intranet with a knowledge graph in Palma in 2026 requires looking beyond the initial budget. Companies need a solution that organizes information, connects people and automates processes, not a simple file repository. To achieve that, it makes sense to understand which technical and business factors determine the price and how to turn that investment into measurable return. Q2BSTUDIO, a custom software and technology development company, works on this type of project with a practical, results-oriented approach.
A knowledge graph structurally represents the relationships between documents, employees, customers, projects and operational data. An intranet built on that foundation enables semantic search, contextual answers, content recommendations and assistants that guide users through their daily work. In 2026, this architecture is especially relevant because it combines generative AI, automation and knowledge management in a single platform. However, its cost depends not only on technology, but also on the starting point of each organization and the scope to be covered.
Recent statistics show that many SMBs use AI tools, but few integrate them into core workflows. In addition, a significant share of companies cites lack of expertise as the main barrier. Therefore, before talking about prices, it is worth knowing whether the project will solve a concrete problem: reducing search time, accelerating onboarding, unifying ERP or CRM information, or facilitating executive decisions. The cost will be different for a pilot solution than for a corporate deployment with cybersecurity and compliance requirements.
The main factors affecting investment are the number of modules and workflows, integrations with existing systems, the required security level, the deployment model, data quality and governance complexity. A simple department intranet with basic search does not cost the same as a corporate portal with AI, Azure OpenAI connectivity, VPN access and advanced auditing.
The first factor is discovery work. Before building anything, it is necessary to map roles, information sources, permissions and processes. This phase makes it possible to define baseline indicators, identify data silos and prioritize use cases. The output is a document with scope and roadmap. Q2BSTUDIO usually performs this stage in one or two weeks through interviews and workshops, avoiding assumptions and aligning expectations before setting the budget.
The development of the portal and the knowledge graph is the core of the project. Unlike a generic template, a custom application allows the company to model its knowledge with its own rules and profiles. This includes user interfaces, conversational search, repositories, administration panels and agents that execute tasks. The design and programming effort depends on the number of features and the level of customization, not on what a plugin can offer.
Another major block is artificial intelligence. For an intranet with a knowledge graph to answer accurately, a well-designed data pipeline is needed: document capture, content splitting, embeddings, vector storage and retrieval-augmented generation (RAG). AI can be delivered through assistants, AI agents that automate tasks and recommendation systems. The most common services are Azure OpenAI, Azure AI Foundry and private models. The cost includes tokens, infrastructure, model tuning and human oversight. Q2BSTUDIO applies these components with artificial intelligence services designed for corporate environments.
Integrations define a large part of the cost. Connecting the knowledge graph to Microsoft SharePoint, Teams, Active Directory, SAP, Odoo, Salesforce, HubSpot or custom APIs requires specific integration work. The more data sources and systems, the greater the maintenance effort. At this point, the decision is whether to replace or extend existing systems. The most cost-effective option is usually to extend through APIs and events so as not to interrupt daily operations.
Security cannot be treated as an add-on. A corporate intranet contains confidential information, intellectual property and personal data. In 2026, serious projects include role-based access control (RBAC), audit logs, encryption in transit and at rest, consent management, right to erasure, GDPR alignment and human oversight for critical decisions. If AI needs to communicate with internal systems, it is common to use VPN tunnels or Azure private endpoints to avoid exposing services. This effort represents a significant part of the budget, but it reduces risk and facilitates compliance.
The deployment model affects recurring cost. Many companies choose the public cloud from AWS or Azure for its elasticity and managed services. Others need a hybrid environment due to regulations or industry requirements, connecting their private network with cloud resources through secure tunnels. Q2BSTUDIO advises on architecture selection based on load, latency, availability and budget, while also sizing support and monitoring.
Another factor that can increase value without raising cost too much is the Business Intelligence layer. With Power BI dashboards or custom dashboards, managers can see usage metrics, response times, incidents and knowledge evolution. This transparency also helps justify the investment and decide future improvements.
In 2026, it is realistic to find intranet projects with a knowledge graph from €5,000 for a limited pilot to more than €40,000 for an enterprise solution with generative AI, complex integrations and Azure deployment. A typical range for a useful corporate deployment is between €25,000 and €60,000. Remember that total cost includes not only development, but also change management, training and maintenance during the first months.
A typical project is structured in clear phases. First, requirements gathering and data analysis. Second, a minimum viable product (MVP) within four to eight weeks to validate the experience with real users. Third, expansion of integrations and security. Fourth, production launch and migration. Finally, a period of support and optimization based on observed metrics. This methodology reduces risk and allows the scope to be adjusted without compromising the entire budget.
Companies generally achieve improvements in process times, reduction of manual tasks and greater leadership visibility. Benefits vary according to technological maturity, but investment is usually recovered within six to twelve months if high-impact use cases are prioritized. In addition, employees stop wasting time searching for information and can focus on more productive activity.
Another aspect that affects profitability is the ownership model. Q2BSTUDIO delivers a client-owned web platform, with an administration portal so business teams can manage prompts, review logs, measure consumption and adjust workflows without depending on a provider for every change. This reduces operating costs and increases autonomy. It is worth clarifying in the contract what happens to the code, data and models when the service ends.
To compare proposals, it is advisable to ask for a proof of concept, a business case with KPIs, a security plan and an integration roadmap. A nice demo is not enough. It is also worth evaluating the team's ability to explain the architecture and support users. A local company like Q2BSTUDIO can combine knowledge of the Palma environment with international technical standards, offering a complete view of development, AI and cybersecurity.
Before requesting a quote, the organization must define which problem it wants to solve and which metrics will demonstrate success. With that clarity, a provider can offer a realistic estimate and a roadmap with deliverables. Q2BSTUDIO offers a free discovery session to guide this decision and prepare a formal proposal with itemized costs.
