Personal Deep Research | Main Trigger Flow

Personal Deep Research Assistant This workflow coordinates a sophisticated, user-friendly research initiation process. It acts as the "front door" for a powerful AI research agent, collecting a user's request, clarifying their intent through an AI-powered dialogue, and then asynchronously triggering a separate, intensive sub-workflow to perform the actual research. The final report is delivered to a pre-configured Notion database. Technologies & Automation Technologies Used - n8n Forms: Used extensively to create a multi-step, interactive user interface for submitting research requests and answering clarification questions. - AI & LangChain: Uses Large Language Models (LLMs) via OpenRouter for two key tasks: generating clarification questions and creating report titles. LangChain nodes provide the framework for prompting and structuring the AI's output. - Notion: Serves as the destination for the final research report, with the workflow creating a new page for each request. - n8n Core Nodes: Utilizes Set, Split Out, and Split in Batches nodes for data manipulation and looping, and the Execute Workflow node for asynchronous processing. What it Automates This workflow automates the entire "onboarding" and setup phase of a complex research task. Instead of a simple query box, it automates: 1. Requirement Gathering: Systematically collects the research topic, desired depth, and breadth. 2. Scope Clarification: Intelligently asks follow-up questions to refine the research prompt, preventing ambiguity and ensuring the final report is more aligned with the user's true intent. 3. Task Management: Creates a placeholder page in Notion for the final report, providing the user with a destination link immediately. 4. Asynchronous Delegation: Triggers a heavy-duty background process (a sub-workflow) to handle the time-consuming research, freeing up the user from having to wait with their browser window open. AI Integration AI is integrated at two critical points to enhance the quality and structure of the research request: 1. AI-Powered Clarification: After the user submits their initial research prompt, the workflow sends this prompt to an LLM (e.g., GPT-4 Mini).