> For the complete documentation index, see [llms.txt](https://docs.glbnxt.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.glbnxt.com/tutorials/video/build-a-sovereign-deep-research-agent.md). # Build a Sovereign Deep Research Agent ### **Protecting Your Competitive Advantage While Using AI** Enterprises frequently use AI to perform deep online research—scanning legislation, competitor reports, academic papers, and patents. However, a critical problem exists: these research findings are often proprietary. When you use standard AI tools for this research, you risk exposing your strategies to foreign vendors who may log your data or use it to train future models. The GLBNXT platform allows you to run open-weight LLMs in a fully sovereign European environment. This ensures your insights remain strictly inside your organization. {% embed url="" %} ### The Deep Research Agent Workflow In this tutorial, we utilize **n8n** on the GLBNXT dashboard to create an agent that automates complex research tasks without external data leakage. The agent is structured in three distinct stages: #### 1. The Planning Stage * **Input:** You provide a specific query or research topic. * **Action:** An LLM analyzes the request and breaks it down into relevant sub-topics or "chapters" to investigate. * **Configuration:** You can specify the depth of the report (e.g., requesting a 5-chapter analysis). #### 2. The Content Stage * **Action:** The agent executes the research plan step-by-step. * **Deep Dive:** It investigates each identified topic individually, gathering data from available sources. * **Traceability:** You can monitor the execution flow in real-time to see exactly what the agent is researching. #### 3. The Finalize Stage * **Compilation:** All collected information is synthesized into a cohesive document. * **Formatting:** The system generates a polished PDF report. * **Delivery:** The final report is automatically emailed directly to your inbox. ### Real-World Example: EU Data Act Analysis In the video demonstration, we task the agent with a complex query: **"Investigate the impact of the EU Data Act on the Dutch hosting market."** **The Result:** * The agent successfully split the query into five distinct research topics. * It automatically generated an **18-page PDF report**. * Crucially, the report included **cited sources** at the end, making the AI's findings verifiable for the organization. ### Why Build This on GLBNXT? * **Zero Data Leakage:** There are no external APIs transferring your research strategies to third parties. * **No Model Training:** Your proprietary findings are never used to train the model for other users. * **Sovereign Infrastructure:** The entire process—from query to PDF generation—runs securely inside a European sovereign platform. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.glbnxt.com/tutorials/video/build-a-sovereign-deep-research-agent.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.