Organizations operating in regulated or security-sensitive environments face significant barriers when adopting AI-based knowledge tools, as confidential business and legal information must not leave controlled infrastructures. As a result, employees often rely on manual searches across large document repositories, leading to inefficient and time-consuming workflows. This situation creates a clear need for AI solutions that combine modern information retrieval with strict data sovereignty, privacy, and compliance requirements.

The project followed a flexible project management approach combining structured planning with iterative execution. After project initiation, objectives, scope, roles, and constraints related to data sovereignty and private cloud deployment were defined. The work was organized using a Work Breakdown Structure and implemented through iterative planning cycles and regular coordination meetings. Technical risks were continuously identified and monitored to ensure alignment with quality, security, and schedule requirements throughout the project.

The project resulted in a functional, private AI platform for secure internal knowledge access. The solution combines a Large Language Model with a Retrieval-Augmented Generation (RAG) architecture, enabling users to query internal documents using natural language. It supports document ingestion from SharePoint and user uploads, automated indexing, and vector-based retrieval. AI-generated responses are provided through a chat interface and are transparently supported by citations referencing the underlying source documents. All data processing, storage, and AI inference are performed entirely within a private cloud environment, ensuring full data ownership, controlled access, and compliance with data protection requirements. The platform is deployed using a centralized Infrastructure-as-Code setup, allowing consistent and repeatable provisioning across environments. For Renacore GmbH, the solution serves as a scalable foundation for future AI-driven knowledge services and a reference architecture for enterprise AI applications in regulated environments.