n8n DeepResearcher
This in-depth research workflow helps users efficiently conduct research on complex topics through automated searches and content scraping, combined with advanced language models. After the user inputs the research topic, the system generates multiple search queries and filters relevant information, supporting dynamic adjustments to the depth and breadth of the research. Ultimately, the gathered information is compiled into a detailed report and automatically uploaded to a cloud management platform, achieving systematic organization and sharing of materials, significantly enhancing research efficiency and quality.
Workflow Name
n8n DeepResearcher
Key Features and Highlights
n8n DeepResearcher is a deep research workflow built on the n8n automation platform, designed to simulate and replicate the OpenAI DeepResearch functionality. It recursively generates search queries, automates web searches and content scraping, and leverages advanced language models for analysis and reasoning. The workflow ultimately produces structured, detailed research reports that are automatically uploaded to Notion for centralized management. Supporting multi-step interactive questioning, it dynamically adjusts research depth and breadth to achieve efficient and systematic investigation of complex topics.
Core Problems Addressed
- Time-consuming and inefficient complex research tasks, with manual efforts struggling to quickly cover vast information sources.
- Fragmented information lacking systematic organization and analysis, making it difficult to produce high-quality reports.
- Traditional automation tools fall short in enabling recursive exploration and multi-round query clarification.
- Difficulty in centralized management and continuous tracking of research outcomes.
n8n DeepResearcher achieves fast, deep, and multidimensional research capabilities through automated recursive search, content scraping, intelligent questioning, and reasoning, significantly reducing time costs while enhancing research quality.
Application Scenarios
- Market research and competitive analysis
- Academic literature reviews
- In-depth exploration of technology trends
- Investment analysis and risk assessment
- Product requirement gathering and user research
- Internal corporate knowledge base updates and expansion
Main Workflow Steps
- Form Trigger: Users submit research topics along with desired research depth and breadth via an n8n form.
- Create Notion Report Page: Automatically generate a blank report page in a specified Notion database to serve as the final report repository.
- Generate and Refine Search Queries: Recursively create multiple unique search queries based on user input and prior research results to cover a broader range of information sources.
- Web Search and Content Scraping: Utilize web scraping services such as APIFY.com to extract structured content from search result pages and filter relevant information.
- Intelligent Clarification Questions: Use OpenAI language models to generate clarification questions related to the research direction; collect user responses via dynamic forms to ensure precise research focus.
- Recursive Research Loop: According to configured depth and breadth, repeatedly generate sub-queries, scrape content, and have the language model distill “learnings” to progressively enrich the research content.
- Aggregation and Reasoning Report Generation: Compile all learnings and employ a reasoning-oriented language model (OpenAI o3-mini) to produce a detailed multi-page research report in Markdown format.
- Format Conversion and Upload: Convert the Markdown report into the Block structure required by the Notion API and iteratively upload it to the corresponding Notion page.
- Status Update and Notification: Automatically update the report status in Notion to “In Progress” and “Completed,” and notify users via the form interface upon research completion.
Involved Systems and Services
- n8n: Automation workflow platform responsible for node orchestration and data flow.
- OpenAI (o3-mini model): Language model used for query generation, clarification questions, learning extraction, and report writing.
- APIFY.com: High-performance web scraping and search service, serving as a cost-effective alternative to Firecrawl.ai.
- Notion: Cloud-based knowledge management platform for storing and presenting final research reports.
- n8n Forms: Interactive tool for collecting user inputs and clarification responses.
- HTTP Request: Used to call external APIs for web data scraping and upload operations.
Target Users and Value Proposition
- Researchers and Analysts: Quickly access vast information, improving research efficiency and depth.
- Product Managers and Marketing Professionals: Automate market research and competitive analysis to support decision-making.
- Content Creators and Academics: Systematically organize materials to generate high-quality content.
- Corporate Knowledge Management Teams: Automatically consolidate external information to keep knowledge bases up-to-date.
- Automation Enthusiasts and Developers: Learn and apply advanced recursive automation and AI integration patterns.
In summary, n8n DeepResearcher is an integrated deep research automation solution combining intelligent search, content scraping, and AI reasoning. It significantly lowers the barriers and time costs associated with complex topic research, making it ideal for professionals and teams seeking fast, high-quality research outcomes.