AI-Powered Job Application Automation
A workflow that transforms a raw job vacancy poster into a personalized application flow, including AI analysis, CV retrieval, validation, and Gmail delivery.
Why this workflow exists.
Job applications can involve repetitive steps: reading vacancy posters, searching for recruiter emails, rewriting application emails, locating the CV, preparing attachments, and sending the message.
Start from the bottleneck.
Use a chat-triggered workflow to turn the vacancy poster into structured information and let automation handle the repeatable preparation steps.
Connect the steps.
The system uses an LLM chain for job information analysis, retrieves a CV from Google Drive, checks whether an email address was found, and sends the prepared message through Gmail when the validation path is true.
From input to output.
Chat message received
Basic LLM Chain + OpenAI Chat Model
Google Drive file retrieval
Email validation: true / false
Gmail message delivery
- n8n
- OpenAI LLM
- Google Drive API
- Gmail API
- Prompt Engineering
The portfolio material documents an end-to-end workflow that can move from a vacancy poster input to a personalized application sent via Gmail.
The same pattern—extract, analyze, validate, retrieve, and dispatch—can be adapted to other repetitive business processes where people repeatedly move information between tools.
Designing useful automation is not only about connecting tools; conditional validation and error prevention are important parts of making a workflow dependable.