About This Architecture

Autonomous hiring pipeline orchestrated by n8n routes candidate resumes through six specialized agents for end-to-end recruitment automation. Agent 1 performs skill shortlisting and resignation risk analysis, Agent 2 verifies profiles via LinkedIn and GitHub APIs, with results stored in Supabase vector database. Agent 3 suggests company matches, Agent 4 conducts skills testing, Agent 5 runs mock interviews, and a fairness score gate above 80% triggers hiring with compensation simulation or routes to Agent 6 for upskilling recommendations. This architecture demonstrates how AI agent orchestration can automate talent screening, assessment, and workforce planning while maintaining fairness thresholds. Fork this diagram on Diagrams.so to customize agent logic, add compliance checks, or integrate your ATS and HRIS systems.

People also ask

How do you architect an AI agent system for autonomous hiring with fairness checks and upskilling recommendations?

Use an n8n orchestrator to route candidates through specialized agents for skill shortlisting, profile verification via LinkedIn/GitHub APIs, company matching, skills testing, and mock interviews. Store verified profiles in Supabase vector DB and gate hiring decisions with an 80% fairness score threshold that triggers either compensation simulation or upskilling pathways.