CV Screening and Matching Analysis Workflow (CV Screening with OpenAI)

This workflow is designed to accelerate the recruitment process by automating the handling of resumes. It downloads resumes from a specified link, extracts the text, and uses advanced AI models to intelligently match and score candidates against job descriptions. The workflow not only provides a percentage of the match but also offers a summary of the candidate's strengths and weaknesses along with hiring recommendations, helping recruiters quickly identify suitable candidates and enhance recruitment efficiency and decision-making accuracy. It is suitable for recruitment agencies and corporate HR teams, significantly reducing the time and cost of manual screening.

Tags

Resume ScreeningSmart Matching

Workflow Name

CV Screening and Matching Analysis Workflow (CV Screening with OpenAI)

Key Features and Highlights

This workflow automates the downloading, text extraction, and intelligent analysis of resumes. Leveraging OpenAI’s advanced language models, it performs matching scoring and comprehensive evaluation between candidate resumes and job descriptions. It not only provides a percentage match score but also delivers concise summaries of strengths and weaknesses along with final hiring recommendations, significantly enhancing recruitment efficiency and decision quality.

Core Problems Addressed

Manual resume screening during recruitment is time-consuming and often lacks objectivity and accuracy. This workflow solves the complexity and subjectivity of traditional resume screening through automation and AI analysis, helping recruiters quickly identify the most suitable candidates while avoiding overlooking top talent or making misjudgments.

Application Scenarios

  • Bulk resume screening for recruitment agencies and HR departments
  • Enhancing automation and intelligence in corporate recruitment teams
  • Situations requiring rapid candidate match evaluation and filtering out unsuitable applicants

Main Process Steps

  1. Trigger Workflow: Manually initiate the test process
  2. Set Variables: Configure resume file URLs and job description text
  3. Download Resume Files: Retrieve candidate resume PDFs from specified URLs
  4. Extract Resume Text: Parse PDF files to extract plain text content
  5. Invoke OpenAI Analysis: Send resume text and job description to OpenAI API to generate match scores and analysis results
  6. Parse and Save Results: Parse the structured JSON returned by OpenAI for subsequent storage or integration

Involved Systems or Services

  • OpenAI API: For intelligent semantic analysis and match scoring
  • Supabase Storage (mentioned in notes, extensible implementation)
  • n8n Core Nodes: HTTP requests, file extraction, variable setting, JSON parsing, etc.

Target Users and Value

  • Recruitment agencies, HR professionals, and hiring teams
  • Enterprises seeking to improve resume screening efficiency and reduce manual costs
  • Employers aiming to leverage AI technology to enhance recruitment accuracy and decision support

This workflow is meticulously developed by community member Mark Shcherbakov and is ideal for users looking to rapidly build intelligent recruitment assistance tools. You can quickly get started with the built-in video tutorials to achieve automated and intelligent resume screening, empowering a more efficient and precise hiring process.

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