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Automate web research & analysis with Oxylabs & GPT for comprehensive reports

VytenisVytenis
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2/3/2026
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Fully automate deep research from start to finish: scrape Google Search results, select relevant sources, scrape & analyze each source in parallel, and generate a comprehensive research report.

Who is this for?

This workflow is for anyone who needs to research topics quickly and thoroughly: content creators, marketers, product managers, researchers, journalists, students, or anyone seeking deep insights without spending hours browsing websites. If you find yourself opening dozens of browser tabs to piece together information, this template will automate that entire process and deliver comprehensive reports in minutes.

How it works

  1. Submit your research questions through n8n's chat interface (include as much context as you need)
  2. AI generates strategic search queries to explore different angles of your topic (customize the number of queries as needed)
  3. Oxylabs scrapes Google Search results for each query (up to 50 results per query)
  4. AI evaluates and selects sources that are the most relevant and authoritative
  5. Content extraction runs in parallel as Oxylabs scrapes each source and AI extracts key insights
  6. Summaries are collected in n8n's data table for final processing
  7. AI synthesizes everything into a comprehensive research report with actionable insights

See the complete step-by-step tutorial on the n8n blog.

Requirements

  • Oxylabs AI Studio API key – Get a free API key with 1000 credits
  • OpenAI API key (or use alternatives like Claude, Gemini, and local Ollama LLMs)

Setup

  1. Install Oxylabs AI Studio as shown on this page
  2. Set your API keys:
    • Oxylabs AI Studio
    • OpenAI
  3. Create a data table
  4. Select the table name in each data table node
  5. Create a sub-workflow:
    • Select the 3 nodes (Scrape content, Summarize content, Insert row)
    • Right-click
    • Select “Convert 3 nodes to sub-workflow”
  6. Edit the sub-workflow settings for for parallel execution:
    • Mode: Run once for each item
    • Options → Add Option → disable “Wait For Sub-Workflow Completion”

Once you finish all these setup steps, you can run the workflow through n8n's chat interface. For example, send the following message:

I'm planning to build a wooden summer house and would appreciate guidance on the process. What are the key considerations I should keep in mind from planning through completion? I'm particularly interested in the recommended construction steps and which materials will ensure long-term durability and quality.

Customize this workflow for your needs

Feel free to modify the workflow to fit the scale and final output your project requires:

  • To reuse this workflow, clear the data table after the final analysis by adding a Data table node with the Delete row(s) action
  • Scale up by processing more search queries, increasing results per query beyond 10, and selecting additional relevant URLs
  • Enable JavaScript rendering in Oxylabs AI Studio (Scraper) node to ensure all content is gathered
  • Adjust the system prompts in LLM nodes to fit your specific research goals
  • Explore other AI Studio apps like Browser Agent for interactive browser control or Crawler for mapping entire websites
  • Connect other nodes like Google Sheets, Notion, Airtable, or webhooks to route results where you need them

n8n Workflow: Basic Chat Trigger with OpenAI and Data Handling

This n8n workflow demonstrates a fundamental interaction pattern: receiving a chat message, processing it with OpenAI, and then handling the response through conditional logic and data manipulation. It serves as a starting point for building more complex AI-driven chat automations.

Description

This workflow automates the process of taking an incoming chat message, sending it to OpenAI for processing, and then conditionally routing the AI's response for further actions or data structuring. It includes steps for data transformation, conditional logic, and a delay mechanism.

What it does

  1. Listens for Chat Messages: The workflow is triggered whenever a chat message is received.
  2. Processes with OpenAI: The received chat message is sent to OpenAI for AI-powered processing (e.g., generating a response, summarizing, classifying).
  3. Edits Fields: The data from the OpenAI response is then passed through an "Edit Fields" (Set) node, likely to transform or select specific parts of the AI's output.
  4. Conditional Routing: An "If" node evaluates the processed data, allowing the workflow to take different paths based on specific conditions (e.g., if a certain keyword is present, or a sentiment score is above a threshold).
  5. Introduces a Delay: A "Wait" node pauses the workflow execution for a specified duration, useful for rate limiting or staggering subsequent actions.
  6. Splits Data: A "Split Out" node is included, which typically breaks down an array of items into individual items, allowing for per-item processing.
  7. Aggregates Data: An "Aggregate" node is present, which combines multiple items into a single item or a structured list, often used after splitting or for final output formatting.
  8. Displays Data: A "Data table" node is used, likely for visualizing or structuring the final processed data, useful for debugging or presenting results.

Prerequisites/Requirements

  • n8n Instance: A running n8n instance (cloud or self-hosted).
  • OpenAI Account & API Key: An OpenAI account with an active API key configured as a credential in n8n.
  • Chat Platform Integration: The "Chat Trigger" node implies an underlying chat platform integration (e.g., Slack, Telegram, Discord, etc.) configured to send messages to this n8n workflow.

Setup/Usage

  1. Import the Workflow: Import the provided JSON into your n8n instance.
  2. Configure Credentials:
    • Set up your OpenAI API Key as an n8n credential.
    • Ensure your chat platform (e.g., Slack, Telegram) is correctly configured to send messages to the "Chat Trigger" webhook URL.
  3. Customize Nodes:
    • Chat Trigger: Ensure it's correctly linked to your desired chat platform.
    • OpenAI: Configure the specific OpenAI model and prompt you wish to use for processing chat messages.
    • Edit Fields: Adjust the fields to be edited or added based on your desired output from OpenAI.
    • If: Define the conditions for routing the workflow based on the OpenAI response.
    • Wait: Adjust the delay duration as needed.
    • Split Out / Aggregate: Configure these nodes if you need to process or combine multiple items from the OpenAI response or subsequent steps.
    • Data table: Configure the columns and data you wish to display.
  4. Activate the Workflow: Once configured, activate the workflow.
  5. Test: Send a message to your configured chat platform to trigger the workflow and observe its execution.

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