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Prism – AI-Powered Recruitment Automation

End-to-end AI recruitment copilot built on n8n, OpenAI, and modern SaaS tools.

Nov 2025
10 min read
Live Demo
Prism – AI-Powered Recruitment Automation

Project Overview

Prism turns the fragmented recruitment process into a cohesive automation layer. It listens to HR inboxes, parses resumes, uses GPT-4 to score candidates, orchestrates interview scheduling via GCal/Gmail, and even drafts final offer/rejection emails based on interviewer feedback. It replaces manual spreadsheet juggling with an intelligent, autonomous pipeline.

100% Auto
Screening
n8n + 5 Apps
Tools
30min/app
Time Saved
Standardized
Consistency

System Architecture

Built on n8n as the central orchestrator. Workflows connect Gmail (Trigger/Comms), OpenAI (Reasoning), Airtable (State/Database), and Google Calendar (Scheduling). Webhooks facilitate handoffs between screening, analytics, scheduling, and decision stages.

System Architecture
Figure 1: System Architecture Diagram

n8n Orchestrator

Low-code engine managing the 4 core workflows

OpenAI Node

GPT-4 for resume parsing, scoring, and decision drafting

Airtable

Structured database for candidate state and analytics

Google Workspace

Gmail and Calendar for seamless communication

Implementation Details

Code Example

javascript
// n8n Code Node Example: Calculate Match Score\nconst candidate = items[0].json;\nconst requirements = ['React', 'Node', 'AI'];\nlet score = 0;\n\nrequirements.forEach(req => {\n  if (candidate.skills.toLowerCase().includes(req.toLowerCase())) {\n    score += 10;\n  }\n});\n\nreturn { json: { ...candidate, match_score: score } };

Agent Memory

Always enforce a JSON schema in your System Prompt when asking the LLM to parse resumes. This ensures n8n downstream nodes can reliably map fields like 'years_experience' without regex hacks.

Workflow

1

Intake: Email triggers workflow; PDF parses to JSON.\n2. Scoring: GPT-4 evaluates fit; updates Airtable.\n3. Analytics: Webhook triggers deep-dive skill matching.\n4. Schedule: Candidate selects GCal slot; invite sent.\n5. Decision: Feedback aggregated; AI recommends Hire/No-Hire.

Workflow Diagram
Figure 2: Workflow Diagram

Results & Impact

"Prism replaced a patchwork of spreadsheets and inbox digging with one coherent AI pipeline. We now spend time talking to people, not chasing info."

Time Saved

Eliminated 15-30m of manual work per candidate.

Fairness

Standardized AI scoring criteria for every applicant.

Velocity

Zero latency handoffs between screening, scheduling, and offers.

About the Author

Akshaay, AI Context Engineer

Akshaay

AI Context Engineer

5+
Projects Delivered
1.5+
Industry Experience

Akshaay

AI Context Engineer

Apex Neural

Developing real-world AI applications with LLMs and structured backends. Creates context-aware solutions using modern AI frameworks. Architecting clean, modular systems for maintainability and performance.

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