Recruitment — AI Candidate Screening Coordinator

Recruiters spend significant time manually reviewing every application before deciding who to move forward with.

Parallel scoring matrix: two independent evaluation tracks run side by side and merge with a Merge node before a single weighted score is calculated.

1. 01Parallel Qualification + Skills Evaluation
2. 02Weighted Scoring & Mandatory Human Review
3. 03Recruiter Output

• n8n
• Form Trigger
• Code (JavaScript)
• If
• Merge
• Set

• Workflow name begins with DEMO | and is inactive.
• No credentials are attached to any node.
• No enabled external send node exists anywhere in this workflow.
• All data is fictional (example.com emails, invented names/addresses).
• Uses only built-in n8n node types.

Real screenshots of the working system — collapsed by default so this page stays readable.

7 structural checks passed, including: Workflow JSON parses (local + server-returned copy); active is false; Name begins with DEMO |; No credentials attached to any node. Structural and logic validation completed. Live n8n execution pending manual safe test.

Classification and scoring logic is deterministic/rule-based rather than a live AI model, by design (provider-independent, fully inspectable, no credential required). No real system of record, messaging channel, or calendar is connected - every downstream action is simulated or drafted, never sent. Live n8n execution has not been triggered as part of this build.

Portfolio demonstration built for a fictional business with fictional data. It is not connected to any real client, system, or customer.

Replace deterministic classification with a real AI model behind the same confidence/human-review pattern where one exists. Connect the mock/simulated steps to real systems of record once reviewed and approved. Wire a real (approved) communication channel behind the draft-message steps.