AI-Driven Interview Assessment Report Generator - n8n Workflow

Recruiters and HR professionals needing automated, standardized interview scoring.
Developers building complex microservices that require internal reporting.
Users looking for advanced examples of how to combine Langchain and custom code within an n8n workflow.
Anyone interested in integrating specialized AI services like OpenRouter into their n8n templates.

Generating accurate, timely performance assessments manually can be resource-intensive. This powerful n8n workflow streamlines the entire process. It is designed to receive interview results or raw performance data through a secure n8n trigger (webhook). Once triggered, it leverages the specialized capabilities of the AI Interview Assessor (a LangChain n8n node) integrated with OpenRouter models to perform deep analysis and score generation. The resulting analysis is then processed by a custom Code n8n node to format the output into a professional report structure. The key value proposition of this n8n workflow is its dual delivery system, ensuring the source application gets an instant response, while stakeholders receive a permanent record via Gmail. This is one of the most effective n8n templates for AI-driven reporting.

The entire process starts with the Receive Interview Data n8n trigger, which is configured as a webhook, waiting for external systems to submit raw data.

1. Trigger: An external application sends interview data (e.g., transcripts, scores) to the webhook n8n trigger.


2. AI Analysis Setup: The data immediately flows into the AI Interview Assessor n8n node, a Langchain Chain LLM type. This node is specifically linked to the OpenRouter Chat Model node, defining the large language model that will execute the assessment criteria.


3. Assessment: The AI processes the raw input against internal criteria (as noted in the workflow comments) to generate a detailed performance assessment and score.


4. Processing & Formatting: The raw AI output is passed to the Process Report Data Code n8n node. This node applies custom scripting logic to clean, structure, and format the assessment into a finalized report, likely generating HTML content.


5. Distribution (Instant): The processed report data splits. One path goes to the Display HTML Report n8n node (RespondToWebhook), sending the formatted report back instantly to the system that initiated the original n8n trigger.


6. Distribution (Email): The second path directs the report data to the Email Assessment Report Gmail n8n node, ensuring a comprehensive summary is delivered to specified stakeholders via email for permanent record keeping. This complete n8n workflow guarantees delivery efficiency.

To deploy this useful n8n workflow, follow these steps:

1. Import: Copy the provided JSON data and paste it directly into your n8n canvas using the 'New' -> 'Import from JSON' option.


2. Webhook Setup: Navigate to the Receive Interview Data n8n trigger node and copy the generated Webhook URL. This is the endpoint external systems will hit.


3. OpenRouter Credentials: Configure the OpenRouter Chat Model n8n node by providing your OpenRouter API key credentials.


4. Gmail Credentials: Set up the credentials for the Email Assessment Report Gmail n8n node. Ensure the service account or linked user has permission to send emails and configure the 'To' and 'Subject' fields to match your reporting needs.


5. Code Review: Review the code within the Process Report Data n8n node. You may need to adjust the formatting logic based on the exact output structure of your AI model.


6. Activation: Once all credentials are set, activate the n8n workflow by toggling the 'Active' switch.

Receive Interview Data (Webhook):
Function: Acts as the starting n8n trigger for the entire n8n workflow, listening for external POST requests containing interview assessment inputs.
Key Configuration: Uses a unique webhook ID to secure the endpoint.
AI Interview Assessor (Langchain Chain LLM):
Function: Orchestrates the AI analysis. This n8n node takes the raw data and uses the linked language model to perform the assessment based on predefined prompts (not visible in JSON, but implied by node type).
Key Configuration: Linked directly to the OpenRouter language model node.
OpenRouter Chat Model (Langchain):
Function: Provides the computational power (LLM) required by the assessor n8n node.
Key Configuration: Requires OpenRouter API credentials.
Process Report Data (Code n8n node):
Function: Customizes the data structure. It takes the assessment results from the AI and processes them into a final, consumable JSON or HTML format before delivery.
Key Configuration: Contains JavaScript logic tailored for data transformation.
Display HTML Report (RespondToWebhook):
Function: Delivers an immediate, formatted response back to the system that initiated the n8n trigger, offering instant feedback.
Key Configuration: Configured to respond with the processed report data.
Email Assessment Report (Gmail n8n node):
Function: Sends the final, detailed report to designated recipients for long-term records, ensuring reliable communication outside the webhook channel.
Key Configuration: Requires linked Gmail credentials and dynamic expression for inputting the report body.