Block 1 - Get RFP Data
- Type / Role
- n8n-nodes-base.extractFromFile - extractFromFile
- Config choices
- Version 1
This workflow is provided as-is. Please review and test before using in production.
This n8n workflow demonstrates how to automate oftern time consuming form filling tasks in the early stages of the tendering process; the Request for Proposal document or "RFP". It does this by uti...
n8n-nodes-base.extractfromfile, @n8n/n8n-nodes-langchain.outputparseritemlist, n8n-nodes-base.splitinbatches, n8n-nodes-base.stickynote, n8n-nodes-base.set, n8n-nodes-base.googledocs, @n8n/n8n-nodes-langchain.lmchatopenai, n8n-nodes-base.slack
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Jimleuk.
Original n8n.io sourceThis n8n workflow demonstrates how to automate oftern time-consuming form filling tasks in the early stages of the tendering process; the Request for Proposal document or "RFP".
It does this by utilising a company's knowledgebase to generating question-and-answer pairs using Large Language Models.
curl --location 'https://<n8n_webhook_url>' \
--form 'id="RFP001"' \
--form 'title="BlueChip Travel and StarBus Web Services"' \
--form 'reply_to="[email protected]"' \
--form 'data=@"k9pnbALxX/RFP Questionnaire.pdf"'
OpenAI assistants is only one approach to hosting a company knowledgebase for AI to use. Exploring different solutions such as building your own RAG-powered database can sometimes yield better results in terms of control of how the data is managed and cost.
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.
| Workflow | Automate Your RFP Process with OpenAI Assistants |
|---|---|
| Complexity | advanced |
| Nodes | 23 |
| Categories | Document Extraction, AI RAG |
| Author | Jimleuk |
| Published | 09 Jul 2024 |
Use the JSON export at /data/workflows/2321/2321.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 n8n workflow demonstrates how to automate oftern time consuming form filling tasks in the early stages of the tendering process; the Request for Proposal document or "RFP". It does this by uti...
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 Document Extraction, AI RAG use case.