Automate Your Applicant Screening with AI
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Streamline your hiring process by automatically screening incoming job applications using AI. This workflow leverages Google Gemini to parse CVs, extract key information, and score candidates against job requirements, saving valuable time for your HR team.
About This Workflow
This n8n workflow revolutionizes candidate sourcing and initial screening by automating the manual tasks often associated with recruitment. It begins by monitoring your Gmail for new applications, specifically those with attachments. The workflow then intelligently extracts CV text, and utilizes Google Gemini's powerful language model to parse and structure crucial applicant data, including name, contact information, education, experience, and skills. It cross-references this extracted data with existing job postings in Airtable, extracting relevant job details like required skills and experience. Finally, another instance of Google Gemini acts as an AI Applicant Scorer, evaluating the candidate's suitability against the job requirements and providing a match score and a concise summary of the reasoning. This significantly reduces the time spent on initial candidate review, allowing recruiters to focus on the most promising applicants.
Key Features
- Automated Application Monitoring: Continuously scans Gmail for new job applications with attachments.
- Intelligent CV Parsing: Extracts key information from PDF CVs using AI.
- Structured Data Extraction: Identifies and structures essential candidate details like skills, experience, and contact info.
- AI-Powered Candidate Scoring: Assesses applicant fit against job requirements with a numerical score and rationale.
- Seamless Data Integration: Connects with Airtable to retrieve job posting details and cross-reference applicant data.
How To Use
- Gmail Trigger Setup: Configure the 'Watch for New Applications' node to connect to your Gmail account and set up filters to detect new applications (e.g., by searching for emails with attachments).
- Job Code Extraction: Set up the 'Extract Job Code' node to parse the job code from the email subject line using a regular expression.
- CV Text Extraction: Connect the 'Read CV (PDF) Text' node to process the downloaded CV attachments.
- AI CV Parsing: Configure the 'AI CV Parser' node, providing the extracted CV text and email subject. Define your desired structured output schema in the
jsonSchemaExample. - Job Post Retrieval: Link the 'Find Job Post' node to your Airtable base and table containing job postings, using the extracted
Job Codeto find the relevant job details. - Data Combination: Use the 'Combine Job & CV Data' node to merge the parsed CV data with the retrieved job post information.
- AI Applicant Scoring: Set up the 'AI Applicant Scorer' node, feeding it the combined job and CV data. Craft a prompt that instructs the AI to compare the applicant's profile against the job requirements and provide a score and summary.
- Structured Output: Configure the 'Structured Output Parser' node to define the expected JSON structure for the AI scorer's output (e.g.,
scoreandfit_summary).
Apps Used
Workflow JSON
{
"id": "5c5440fa-11c9-49c0-b851-482db3dadbeb",
"name": "Automate Your Applicant Screening with AI",
"nodes": 8,
"category": "Operations",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
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ID: 5c5440fa-11c9...
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