The cost of a corporate intranet with AI in Las Palmas in 2026 depends on specific variables: the number of employees who will use it, the amount of internal processes being digitized, integrations with existing systems, and the level of security required. A corporate intranet is not just a document portal; it is the digital backbone of an organization, where knowledge is managed, approval flows are automated, and remote teams are connected.
Q2BSTUDIO approaches this kind of project with a methodology that combines software engineering, cloud architecture, and experience in artificial intelligence. Before talking about budgets, the team carries out a discovery session to understand how each department works, which tools it uses, and where the main bottlenecks are. That phase makes it possible to size the solution correctly and avoid unnecessary investment: many companies ask for an advanced intranet when what they really need is an intelligent search layer over documents and existing records.
The cost of a corporate intranet with artificial intelligence can be organized into an indicative range. Focused solutions, including a semantic search engine, a news portal, and a few approval flows, usually move between 15,000 and 40,000 euros. More complex projects, with AI agents, ERP connectivity, integration with Azure AI Foundry or AWS, activity auditing, and private network deployment, can exceed 70,000 euros and require a continuous support model.
The items that most influence the price are integrations. Connecting the intranet to Microsoft Teams, SharePoint, Active Directory, SAP, Odoo, or a custom CRM is not a trivial task. Each system has a different API, different levels of maturity, and particular security requirements. Q2BSTUDIO develops custom software that acts as a bridge between the intranet and those systems, preventing the organization from having to abandon tools in which it has already invested time and money.
Security is another critical factor in the budget. An intranet with AI that handles customer data, financial information, or internal documentation must comply with data protection principles and corporate governance policies. At this point, Q2BSTUDIO’s experience in cybersecurity enables role-based access control, audit logs, end-to-end encryption, and real-time monitoring systems. For clients operating in regulated sectors, VPN tunnels and private endpoints in Azure or AWS cloud are used, so sensitive information does not travel through public networks.
The artificial intelligence component is not limited to a search engine. In 2026, companies that truly obtain return on investment use language models connected to their own knowledge base. This means an employee can ask the intranet how to process an invoice, what procedure a new customer onboarding follows, or where the latest version of a contract is, and receive a direct answer with the cited source. To achieve this, Q2BSTUDIO combines RAG, embeddings, and models deployed on private infrastructure or in the cloud, avoiding full dependence on public APIs that can generate variable costs and confidentiality issues.
AI agents are another functionality gaining importance in intranet projects. It is not only about answering questions: an agent can create a ticket, request a signature, update a record in Salesforce, or generate a report for management. These automations reduce manual work and allow people to focus on higher-value tasks. The development effort of these agents depends on the number of actions they must execute and the complexity of the associated business rules.
Q2BSTUDIO also incorporates BI and Business Intelligence capabilities into the intranet. When an executive accesses the portal, they not only find documents: they find activity indicators, deadline compliance, and automatic alerts. Through dashboards built with Power BI or similar tools, the organization has a clear view of what is happening in each area, which facilitates decision-making and avoids unproductive meetings in which reliable data is not available.
The recommended delivery model for this type of project is phased. A first deliverable can be operational in a few weeks and serve as a basis for validating user experience and the accuracy of search results. Then additional modules are incorporated, such as approval flows, ERP/CRM integrations, or automation agents. This way of working reduces financial risk and allows the client to verify real progress before expanding the investment.
Companies in Las Palmas de Gran Canaria have a differentiating characteristic: they operate in an ecosystem made up of local headquarters, international clients, and strong activity in tourism, commerce, and logistics. A corporate intranet with AI helps connect teams that work in different time zones, preserve knowledge when there is staff turnover, and offer faster service to the end customer. For a company in the tourism sector, for example, an AI agent can instantly answer internal questions about bookings, suppliers, or quality protocols.
The return on investment is observed in reduced search times, fewer duplicate documents, and faster resolution of internal issues. There is also an indirect benefit: employees trust corporate systems more when they find the right information at the right time. That cultural change has an impact that is difficult to quantify at the beginning, but very visible in daily productivity.
Q2BSTUDIO’s recommendation is to start with a specific, measurable use case: for example, automating access to a policy manual or accelerating the processing of internal requests. From there, the solution grows naturally and on a solid technical base. Artificial intelligence applied to business software stops being a promise and becomes another module of the intranet, audited, controlled, and aligned with business objectives.
Anyone evaluating this type of investment in 2026 should pay attention to two aspects: the provider’s ability to understand the business and its technical maturity in AI, cloud, and security. Q2BSTUDIO combines both perspectives and offers support that goes beyond initial development, including internal team training, process documentation, and an administration portal so the company can manage its own prompts and usage metrics. The result is an intranet with AI that adapts to the organization, not the other way around.
