Block 1 - Structured Output Parser
- Type / Role
- @n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
- Config choices
- Version 1.2
This workflow is provided as-is. Please review and test before using in production.
This template attempts to replicate OpenAI's DeepResearch feature which, at time of writing, is only available to their pro subscribers. An agent that uses reasoning to synthesize large amount...
@n8n/n8n-nodes-langchain.outputparserstructured, n8n-nodes-base.set, @n8n/n8n-nodes-langchain.lmchatopenai, n8n-nodes-base.formtrigger, @n8n/n8n-nodes-langchain.chainllm, n8n-nodes-base.splitout, n8n-nodes-base.noop, n8n-nodes-base.splitinbatches
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Jimleuk.
Original n8n.io sourceThis template attempts to replicate OpenAI's DeepResearch feature which, at time of writing, is only available to their pro subscribers.
> An agent that uses reasoning to synthesize large amount of online information and complete multi-step research tasks for you. Source
Though the inner workings of DeepResearch have not been made public, it is presumed the feature relies on the ability to deep search the web, scrape web content and invoking reasoning models to generate reports. All of which n8n is really good at!
Using this workflow, n8n users can enjoy a variation of the Deep Research experience for themselves and their teams at a fraction of the cost. Better yet, learn and customise this Deep Research template for their businesses and/or organisations.
Check out the generated reports here: https://jimleuk.notion.site/19486dd60c0c80da9cb7eb1468ea9afd?v=19486dd60c0c805c8e0c000ce8c87acf
For more detailed reports, increase depth and breadth but be warned the workflow will take exponentially longer and cost more to complete. The recommended defaults are usually good enough.
Depth=1 & Breadth=2 - will take about 5 - 10mins. Depth=1 & Breadth=3 - will take about 15 - 20mins. Dpeth=3 & Breadth=5 - will take about 2+ hours!
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.
Showing the first 24 of 85 workflow blocks. Download the JSON for the full node graph.
| Workflow | Host your own AI deep research agent with n8n, Apify and OpenAI o3 |
|---|---|
| Complexity | advanced |
| Nodes | 85 |
| Categories | Market Research, AI Chatbot |
| Author | Jimleuk |
| Published | 11 Feb 2025 |
Use the JSON export at /data/workflows/2878/2878.json as the source template for this automation.
Open n8n, import the downloaded JSON, and review each node before activating the workflow.
Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.
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.
This template attempts to replicate OpenAI's DeepResearch feature which, at time of writing, is only available to their pro subscribers. An agent that uses reasoning to synthesize large amount...
Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.
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, AI Chatbot use case.