AI-Powered HR Automation Pipeline

This workflow is designed for HR professionals, recruiters, and talent acquisition teams who are looking to streamline the process of handling job applications. It is particularly beneficial for those dealing with a high volume of applications, as it automates the extraction and evaluation of candidate information, saving time and enhancing efficiency.

This workflow addresses the challenge of manually processing job applications. By automating the extraction of key information from CVs, it significantly reduces the time spent on initial candidate evaluations. Furthermore, it provides a structured approach to assess candidates against a predefined profile, ensuring that the hiring process is both efficient and effective.

1. Form Submission: The workflow begins when a candidate submits their CV via a form titled 'Send CV', which requires their Name, Email, and a CV file in PDF format.

2. File Extraction: Upon submission, the CV is extracted using the Extract from File node, focusing on PDF files to retrieve textual content.

3. Information Extraction: The extracted text is processed to identify key attributes such as Educational qualifications, Job History, and Skills using the Qualifications node.

4. Personal Data Extraction: Additional personal information, including City, Birthdate, and Telephone, is extracted through the Personal Data node.

5. Data Merging: The information gathered from both extraction nodes is merged to create a comprehensive candidate profile.

6. Summarization: A summarization chain condenses the candidate's information into a concise format, ensuring clarity and brevity.

7. Profile Comparison: The workflow then compares the candidate's profile against a predefined Profile Wanted set by the hiring agency, which specifies desired qualifications and experience.

8. Candidate Evaluation: An HR Expert node evaluates the candidate based on the summarized information and the profile requirements, assigning a score from 1 to 10 and providing motivational feedback.

9. Data Storage: Finally, the results, including candidate details and evaluation, are appended to a Google Sheets document for easy tracking and reference, ensuring all data is organized and accessible.