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Deep research agent - automated research & Notion report builder

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Deep research agent - automated research & Notion report builder preview
Open on n8n.io

Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

This workflow acts as an AI powered research assistant that takes a topic from the user, performs multi step intelligent research, and stores the final report in Notion. It uses advanced search, co...

Best for

  • Market Research automation workflows
  • Multimodal AI automation workflows
  • advanced n8n builders looking for reusable templates

Tools used

@n8n/n8n-nodes-langchain.memorybufferwindow, @n8n/n8n-nodes-langchain.outputparserstructured, n8n-nodes-base.switch, @n8n/n8n-nodes-langchain.agent, n8n-nodes-base.splitout, n8n-nodes-base.splitinbatches, n8n-nodes-base.httprequest, n8n-nodes-base.set

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Aziz B.

Original n8n.io source

1.1 Workflow description

Title
Deep research agent - automated research & Notion report builder
Workflow name
Deep research agent - automated research & Notion report builder

Overview

  • This workflow acts as an AI-powered research assistant that takes a topic from the user, performs multi-step intelligent research, and stores the final report in Notion. It uses advanced search, content extraction, and AI summarization to deliver a high-quality research report—fully automated from query to publication.

How It Works

  • User Interaction

    • The workflow starts by asking the user what topic they want to research.
    • A “Strategy Agent” asks 2–3 clarifying questions to refine the scope.
    • Once the user confirms, it creates a Notion database page with the research title.
  • Search Query Generation

    • Generates up to 3 relevant search queries for the given topic.
  • Data Gathering (Loop over each query)

    • Sends the query to Tavily Search API to find the most relevant blogs/articles.
    • Picks the top-matched link and uses Tavily again to extract its content.
    • Repeats the process for all 3 queries.
  • Report Compilation

    • Aggregates extracted content from all sources.
    • A Final Report Agent creates a well-structured research report in Markdown.
    • Converts Markdown → HTML → splits into chunks.
    • Pushes each chunk into the Notion report page.
  • Delivery

    • Sends the final Notion report link back to the user.

How to Use

  • This workflow is triggered via Webhook.
  • Attach the provided webhook URL to any application, form, or chatbot to collect the user’s topic.
  • Once triggered, the workflow will run automatically and deliver the research link without any manual steps.

Requirements

To use this workflow, you’ll need:

  • n8n account (self-hosted or cloud)
  • Notion account with a database where reports will be stored
  • Tavily API Key – for search & content extraction
  • OpenRouter API key or OpenAI API key – for AI agents & report generation
  • Google Gemini API Key – for converting Markdown to HTML and splitting content for Notion
  • Notion database ID connected in n8n

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - Simple Memory

Type / Role
@n8n/n8n-nodes-langchain.memoryBufferWindow - memoryBufferWindow
Config choices
Version 1.3

Block 2 - Structured Output Parser

Type / Role
@n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices
Version 1.2

Block 3 - Switch

Type / Role
n8n-nodes-base.switch - switch
Config choices
Version 3.2

Block 4 - Strategy Agent

Type / Role
@n8n/n8n-nodes-langchain.agent - agent
Config choices
Version 1.8

Block 5 - Search Query Agent

Type / Role
@n8n/n8n-nodes-langchain.agent - agent
Config choices
Version 1.8

Block 6 - Structured Output Parser1

Type / Role
@n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices
Version 1.2

Block 7 - Split Out

Type / Role
n8n-nodes-base.splitOut - splitOut
Config choices
Version 1

Block 8 - Loop Over Queries

Type / Role
n8n-nodes-base.splitInBatches - splitInBatches
Config choices
Version 3

Block 9 - HTTP Request

Type / Role
n8n-nodes-base.httpRequest - httpRequest
Config choices
Version 4.2

Block 10 - Edit Fields

Type / Role
n8n-nodes-base.set - set
Config choices
Version 3.4

Block 11 - OpenAI

Type / Role
@n8n/n8n-nodes-langchain.openAi - openAi
Config choices
Version 1.8

Block 12 - HTTP Request1

Type / Role
n8n-nodes-base.httpRequest - httpRequest
Config choices
Version 4.2

Block 13 - Aggregate

Type / Role
n8n-nodes-base.aggregate - aggregate
Config choices
Version 1

Block 14 - OpenAI1

Type / Role
@n8n/n8n-nodes-langchain.openAi - openAi
Config choices
Version 1.8

Block 15 - Notion

Type / Role
n8n-nodes-base.notion - notion
Config choices
Version 2.2

Block 16 - Notion1

Type / Role
n8n-nodes-base.notion - notion
Config choices
Version 2.2

Block 17 - HTTP Request2

Type / Role
n8n-nodes-base.httpRequest - httpRequest
Config choices
Version 4.2

Block 18 - Convert to HTML

Type / Role
n8n-nodes-base.markdown - markdown
Config choices
Version 1

Block 19 - HTML to Array

Type / Role
n8n-nodes-base.set - set
Config choices
Version 3.4

Block 20 - Tags to Items

Type / Role
n8n-nodes-base.splitOut - splitOut
Config choices
Version 1

Block 21 - Notion Block Generator

Type / Role
@n8n/n8n-nodes-langchain.chainLlm - chainLlm
Config choices
Version 1.5

Block 22 - Google Gemini Chat Model

Type / Role
@n8n/n8n-nodes-langchain.lmChatGoogleGemini - lmChatGoogleGemini
Config choices
Version 1

Block 23 - Parse JSON blocks

Type / Role
n8n-nodes-base.set - set
Config choices
Version 3.4

Block 24 - Valid Blocks

Type / Role
n8n-nodes-base.filter - filter
Config choices
Version 2.2

Showing the first 24 of 43 workflow blocks. Download the JSON for the full node graph.

3. Summary Table

Workflow Deep research agent - automated research & Notion report builder
Complexity advanced
Nodes 43
Categories Market Research, Multimodal AI
Author Aziz B
Published 08 Aug 2025

4. Reproducing the Workflow from Scratch

  1. 1. Download the workflow JSON

    Use the JSON export at /data/workflows/7160/7160.json as the source template for this automation.

  2. 2. Import the template into n8n

    Open n8n, import the downloaded JSON, and review each node before activating the workflow.

  3. 3. Configure credentials and variables

    Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.

  4. 4. Test with sample data

    Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.

  5. 5. Activate and monitor

    Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Frequently asked questions

What does Deep research agent - automated research & Notion report builder do?

This workflow acts as an AI powered research assistant that takes a topic from the user, performs multi step intelligent research, and stores the final report in Notion. It uses advanced search, co...

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Market Research, Multimodal AI use case.