This n8n workflow automates the process of handling job applications, from receiving data via webhook to candidate shortlisting and data updating in ERPNext. It streamlines recruitment by integrating file handling, AI-powered candidate evaluation, and communication notifications.

The workflow begins with a webhook trigger for new applications. It downloads the resume file, which can be in PDF, DOC, or JPG format, and extracts text content using dedicated nodes. Depending on the resume file type, different extraction methods are employed.

The core of the workflow involves an AI agent (using LangChain’s AI models) that compares the resume content against the job description provided. The AI assesses whether the candidate is a strong, moderate, or weak fit, scores the alignment, and provides a justification.

Extracted data (fit level, score, rating, justification) is then formatted into specific fields created in ERPNext. Based on the AI’s assessment, the candidate is either accepted or rejected: failed candidates are marked as rejected, while successful ones are updated with additional details and sent notifications via email, WhatsApp, or Outlook.

Additionally, the workflow includes logic to handle scenarios where resume links are missing or the application is not aligned with a job opening, ensuring proper status updates in ERPNext.

This workflow is highly practical for recruitment teams seeking to automate the initial candidate screening, improve decision consistency, and accelerate communication with applicants.

Node Count	>20 Nodes
Nodes Used	@n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmChatGoogleGemini, code, erpNext, extractFromFile, httpRequest, if, merge, microsoftOutlook, set, stickyNote, switch, webhook, whatsApp