This n8n workflow streamlines the process of evaluating candidate resumes through AI-driven image analysis and natural language processing. The workflow starts with manual trigger for testing purposes, allowing users to initiate the process whenever needed. It downloads a candidate’s resume PDF from Google Drive, which can be replaced with other sources like email or ATS systems. The PDF is then converted into an image via Stirling PDF API, resizing the image for faster processing.
The image is fed into a multimodal large language model (Google Gemini), capable of understanding visual data, to analyze the resume. The analysis focuses on assessing if the candidate’s skills match the role, in this case, a plumber, and whether they qualify for an interview. Results from the analysis are parsed into a structured JSON output.
A conditional node checks the qualification status. If the candidate is qualified, the process can proceed to further stages, such as scheduling interviews or sending follow-up emails. Throughout the workflow, sticky notes provide detailed guidance and contextual explanations, aiding users in understanding each stage.
This automation is particularly useful in HR pipelines to ensure fair, bias-free, and efficient candidate screening by leveraging AI to interpret resumes, reducing manual effort and increasing accuracy in early-stage candidate evaluation.
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