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In 2026, companies seeking to transform their internal communication and streamline resource management face a fundamental challenge: how to take an intranet with an internal marketplace to production without compromising security, scalability, or user experience. The digitalization of corporate workflows is no longer an option but a competitive necessity, and in this context, solutions integrating advanced technologies such as artificial intelligence, AI agents, and RAG-based (Retrieval-Augmented Generation) assistants emerge. However, the leap from a validated concept to a real production environment requires a methodical approach that combines robust architecture, integrations with legacy systems, and clear governance.
This is where Q2BSTUDIO positions itself as the ideal technical partner for organizations based in Seville or operating from this region. Their proposal goes beyond developing custom applications: they offer a complete cycle that includes architecture review, deployment planning, CI/CD configuration, perimeter security, observability, database analysis, and post-launch support. This approach is particularly relevant when the intranet incorporates an internal marketplace that must manage catalogs, transactions, user roles, and connectivity with ERPs such as SAP, Odoo, or Microsoft Dynamics, as well as collaboration tools like SharePoint and Teams.
Market figures reinforce the opportunity: according to the Goldman Sachs SMB AI Integration 2026 report, 76% of SMEs already use AI tools, but only 14% have integrated them into their core processes. Furthermore, 31% of small and medium-sized enterprises identify lack of technical knowledge as the main adoption barrier, according to the Bookipi survey. In this scenario, having a team that masters both AI for businesses and cybersecurity makes the difference. Q2BSTUDIO deploys secure intranets using AWS and Azure cloud services, VPN tunnels, and private endpoints in Azure, ensuring that private language models and RAG systems interact with on-premise data without exposing sensitive information.
The adoption process begins with a discovery phase where current workflows, system dependencies, and baseline KPIs are mapped. From there, Q2BSTUDIO delivers a minimum viable product (MVP) within 4 to 8 weeks, naturally integrating artificial intelligence capabilities, AI agents, and Power BI for real-time indicator visualization. The final platform includes role-based access control, audit logging, GDPR compliance, and human-in-the-loop checkpoints when automation requires it.
The quantifiable results typically achieved with this methodology are compelling: a 20% to 45% reduction in process cycle times, a 15% to 35% decrease in operational costs for target workflows, and a 30% to 60% reduction in repetitive manual tasks. Additionally, unified dashboards provide strategic visibility to management, facilitating data-driven decision-making. For the financial officer, Q2BSTUDIO prepares a written business case with KPIs, return timeline, and risk register before starting development, simplifying budget approval.
Regarding production, the maturity checklist includes architecture and dependency review, database analysis (migrations, indexes, and security), authentication and authorization with RBAC, CI/CD strategy with staging and rollback environments, observability with monitoring and performance testing, and a documented operational handover. All of this is delivered with a customized web portal that allows business users to configure prompts, monitor costs, and operate AI flows without relying on the engineering team for every change. Thus, the client company achieves real autonomy in managing its custom software.
For companies operating in Seville and looking for a partner with proven experience in high-level production environments, Q2BSTUDIO offers a free 30-minute discovery session. There, specific needs are analyzed, and a roadmap is outlined that combines business intelligence services, artificial intelligence, and an internal marketplace designed to grow with the organization.
