Automatic Candidate Interview Scoring and Database Update - n8n Workflow

• HR Professionals and Recruiters managing high-volume candidate screening.


• Technical Leads needing objective, automated evaluation metrics.


• Users searching for robust n8n templates that combine AI agents with Google Sheets operations.


• Automation engineers requiring a reliable, custom AI evaluation n8n workflow.

Manually scoring candidate questionnaires is time-consuming and prone to human bias. This automated n8n workflow solves this by providing immediate, objective evaluation powered by a modern AI model.

The system starts with an n8n trigger monitoring new submissions via Google Sheets. Once a new response is detected, the workflow sends the answers to an Azure OpenAI GPT-4o-mini agent for analysis. The agent scores the responses (0-30 points) based on criteria like knowledge depth and communication clarity, and returns detailed takeaways.

After parsing the AI results, the n8n workflow retrieves the candidate's existing profile score from a central database sheet. It then calculates a comprehensive 'final score' (Existing Score + Questionnaire Score) and updates the master candidate database instantly. This n8n workflow ensures consistent, fast, and scalable candidate evaluation, providing better insights for hiring decisions.

This comprehensive n8n workflow follows a seven-step process:

1. Trigger Activation (Google Sheets Trigger): The process begins when the Google Sheets Trigger n8n node monitors the designated questionnaire response sheet every minute for new row insertions (new submissions).


2. AI Evaluation (Langchain Agent): The incoming questionnaire data is passed to the 'AI Questionnaire Evaluator' n8n node, which acts as a structured agent. It uses a predefined prompt instructing the AI to evaluate answers and output a structured JSON object with questionnairescore and keytakeaways.


3. Model Selection (Azure OpenAI): The agent uses the configured Azure OpenAI GPT-4o-mini model, ensuring high-quality and cost-effective analysis for this specific n8n workflow.


4. Data Parsing (Code): The AI's output is often text wrapped in markdown code fences. The 'Parse AI Evaluation Results' Code n8n node cleans this output by removing the fences and safely converting the resulting string into a usable JSON object.


5. Profile Lookup (Google Sheets): The workflow then uses the candidate's name to look up their existing data, including their current evaluation 'Score', in the central 'Resume store' Google Sheet.


6. Score Calculation (Set): The 'Calculate Combined Scores' n8n node combines the retrieved existing score with the new questionnaire_score generated by the AI to create the 'final score'. This ensures a complete assessment within the n8n template.


7. Database Update (Google Sheets): Finally, the 'Update Candidate Database' n8n node updates the candidate's row in the 'Resume store' sheet, adding the new 'Questionarie Score' and the calculated 'Final score'. This completes the automated n8n workflow cycle.

To deploy this advanced n8n workflow, follow these steps:

1. Import the n8n Workflow: Copy the provided JSON data and paste it into your n8n instance using the 'New' button and selecting 'Import from JSON'.


2. Google Sheets Credentials: You will need two separate Google Sheets credentials configured:

1. Azure OpenAI Credentials: Configure your Azure OpenAI API key and endpoint credentials for the 'Azure OpenAI GPT-4 Model' n8n node. This connection is vital for the AI evaluation part of the n8n template.


2. Update Sheet IDs: Ensure the Document IDs and Sheet Names in all Google Sheets n8n nodes are updated to match your specific questionnaire submission sheet and your central candidate database sheet. This is crucial for the n8n trigger and subsequent operations.


3. Customize AI Agent: Review the system message and prompt in the 'AI Questionnaire Evaluator' n8n node to match the specific questions and evaluation criteria of your current hiring role.

• Monitor New Questionnaire Responses (Google Sheets Trigger): This is the starting n8n trigger. It polls the specified 'BD Questionarie' sheet (Form Responses 1 tab) every minute to detect new candidate submissions.


• AI Questionnaire Evaluator (Langchain Agent n8n node): Utilizes the LLM connection to process candidate answers (A1, A2). It operates with a strict system message requiring JSON output containing questionnairescore and keytakeaways.


• Azure OpenAI GPT-4 Model (Langchain Chat n8n node): Configured as the underlying LLM using the gpt-4o-mini model, ensuring the required intelligence for structured evaluation within this n8n workflow.


• Parse AI Evaluation Results (Code n8n node): A critical step that uses custom JavaScript to strip surrounding code fences (e.g., ```json) from the AI output and perform robust JSON parsing, guaranteeing data quality for the rest of the n8n workflow.


• Lookup Candidate Profile Data (Google Sheets n8n node): Performs a lookup operation on the 'Resume store' sheet to fetch the candidate's existing total 'Score' necessary for the final calculation.


• Calculate Combined Scores (Set n8n node): This n8n node handles the core calculation, dynamically combining the existing score with the AI-generated score using expressions to produce the 'final score' and setting the individual 'Questionarie Score'.


• Update Candidate Database (Google Sheets n8n node): The final step. It uses the 'appendOrUpdate' operation, matching on the candidate 'Name', to persist the new 'Final score' and 'Questionarie Score' back into the central database. This completes the functionality of the n8n template.