Block 1 - Daily Hiring Analytics Trigger
- Type / Role
- n8n-nodes-base.scheduleTrigger - scheduleTrigger
- Config choices
- Version 1.3
How It Works This workflow automates end to end recruitment operations for HR teams, talent acquisition specialists, and hiring managers facing high volume candidate processing challenges. It solve...
n8n-nodes-base.scheduletrigger, n8n-nodes-base.set, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmchatopenai, @n8n/n8n-nodes-langchain.outputparserstructured, @n8n/n8n-nodes-langchain.agenttool, n8n-nodes-base.switch, n8n-nodes-base.datatable
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Cheng Siong Chin.
Original n8n.io sourceThis workflow automates end-to-end recruitment operations for HR teams, talent acquisition specialists, and hiring managers facing high-volume candidate processing challenges. It solves the critical problem of manual interview coordination, inconsistent candidate evaluation, and scattered assessment data across multiple platforms.The system orchestrates a seamless pipeline: triggers initiate workflow execution, configuration nodes prepare analytics parameters, and Former Analytics Agent structures the evaluation framework. The Orchestration Agent intelligently routes candidates through specialized AI assessment modules—including sourcing verification, simulated interviews, and competency evaluation—each powered by different AI models (OpenAI GPT-4, Claude) optimized for specific assessment criteria. Consolidated insights automatically populate Google Sheets for centralized tracking, while Gmail notifications keep stakeholders informed. Critical alerts route to HR teams via Slack integration, ensuring immediate visibility into high-priority candidates and assessment bottlenecks, dramatically reducing time-to-hire while improving evaluation consistency.
Developer account with API access, OpenAI API key (GPT-4 enabled)
High-volume technical recruitment campaigns requiring standardized assessment frameworks
Modify AI agent prompts to align with specific role competencies
Reduces time-to-hire by 60% through parallel AI assessments
This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.
Showing the first 24 of 33 workflow blocks. Download the JSON for the full node graph.
| Workflow | Orchestrate AI-driven hiring analytics and candidate assessment with GPT-4, Claude, Google Sheets, Gmail and Slack |
|---|---|
| Complexity | advanced |
| Nodes | 33 |
| Categories | HR, AI RAG |
| Author | Cheng Siong Chin |
| Published | 12 Feb 2026 |
Use the JSON export at /data/workflows/13352/13352.json as the source template for this automation.
Open n8n, import the downloaded JSON, and review each node before activating the workflow.
Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.
Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.
Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.
How It Works This workflow automates end to end recruitment operations for HR teams, talent acquisition specialists, and hiring managers facing high volume candidate processing challenges. It solve...
Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.
Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your HR, AI RAG use case.