n8n Developer for Quotation Database Construction
Budget: €30 – €250 EUR
Title: n8n + Help Scout PDF Quote Extraction System
Overview
I am looking for an experienced n8n automation developer to complete and debug an existing workflow that extracts quotation data from Help Scout conversations and builds a searchable pricing database.
Current Status
I already have an n8n workflow partially built:
Help Scout Conversations
→ Threads
→ Find PDF Attachments
→ Download PDF
→ Extract PDF Text
→ OpenAI Extraction
→ Normalize Data
→ Google Sheets / Database
The workflow is running, but I am having issues with:
* Finding PDF attachments reliably from Help Scout
* Accessing attachment metadata from conversation threads
* Downloading attached quotation PDFs
* Extracting structured quote data accurately
* Building a clean searchable quote database
Goal
Create a system that processes historical Help Scout conversations and extracts pricing information from quotation PDFs.
The final database should contain fields such as:
* Product category
* Product name
* Quantity
* Unit price
* Total price
* Print method
* Embroidery information
* Customer name
* Quote date
* Source PDF
* Help Scout conversation ID
Technical Requirements
Experience with:
* n8n
* Help Scout API
* OpenAI API
* PDF extraction
* Google Sheets, Airtable or Supabase
* Data normalization
Deliverables
1. Fix Help Scout attachment extraction
2. Download and process quotation PDFs automatically
3. Extract structured quote information using AI
4. Store extracted data in a database (Google Sheets initially)
5. Document the workflow
6. Provide recommendations for scaling to a vector database (Pinecone or Supabase)
Bonus
Experience with:
* RAG systems
* Pinecone
* Supabase Vector Search
* AI-powered quote recommendation systems
End Goal
I want an AI assistant that can receive inquiries such as:
"Ég þarf 50 boli með logo" (in Icelandic meaning: I need 50 t-shirts)
and instantly retrieve similar historical quotations, showing:
* closest quantity below
* closest quantity above
* example pricing
* recommended customer response
The objective is to build a reliable pricing intelligence system based on thousands of historical quotations.
Please include:
* Relevant n8n projects
* Experience with Help Scout
* Estimated hours
* Fixed-price estimate
Overview
I am looking for an experienced n8n automation developer to complete and debug an existing workflow that extracts quotation data from Help Scout conversations and builds a searchable pricing database.
Current Status
I already have an n8n workflow partially built:
Help Scout Conversations
→ Threads
→ Find PDF Attachments
→ Download PDF
→ Extract PDF Text
→ OpenAI Extraction
→ Normalize Data
→ Google Sheets / Database
The workflow is running, but I am having issues with:
* Finding PDF attachments reliably from Help Scout
* Accessing attachment metadata from conversation threads
* Downloading attached quotation PDFs
* Extracting structured quote data accurately
* Building a clean searchable quote database
Goal
Create a system that processes historical Help Scout conversations and extracts pricing information from quotation PDFs.
The final database should contain fields such as:
* Product category
* Product name
* Quantity
* Unit price
* Total price
* Print method
* Embroidery information
* Customer name
* Quote date
* Source PDF
* Help Scout conversation ID
Technical Requirements
Experience with:
* n8n
* Help Scout API
* OpenAI API
* PDF extraction
* Google Sheets, Airtable or Supabase
* Data normalization
Deliverables
1. Fix Help Scout attachment extraction
2. Download and process quotation PDFs automatically
3. Extract structured quote information using AI
4. Store extracted data in a database (Google Sheets initially)
5. Document the workflow
6. Provide recommendations for scaling to a vector database (Pinecone or Supabase)
Bonus
Experience with:
* RAG systems
* Pinecone
* Supabase Vector Search
* AI-powered quote recommendation systems
End Goal
I want an AI assistant that can receive inquiries such as:
"Ég þarf 50 boli með logo" (in Icelandic meaning: I need 50 t-shirts)
and instantly retrieve similar historical quotations, showing:
* closest quantity below
* closest quantity above
* example pricing
* recommended customer response
The objective is to build a reliable pricing intelligence system based on thousands of historical quotations.
Please include:
* Relevant n8n projects
* Experience with Help Scout
* Estimated hours
* Fixed-price estimate
Related categories:
PHP
C# Programming
Software Architecture
MySQL
Data Extraction
Airtable
Google Sheets
Automation
Database Management
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