The $14.60 Problem Nobody Talks About
Most HR leaders know their cost-per-hire. Few know their cost-per-screen.
When we audited a mid-sized SaaS company's recruitment pipeline, we found they were spending $14.60 to screen each candidate. For 500 applications per month, that's $7,300 — before a single interview.
The culprit? Manual resume reviews (6 min/candidate × $73/hr recruiter rate), scattered ATS workflows, and brittle automation scripts that failed 40% of the time.
Three months after deploying Vectorhire's multi-agent system, that number dropped to $1.90.
Here's the technical breakdown — with sequence diagrams, error-handling patterns, and reproducible cost models.
┌─────────────┐ ┌──────────────┐ ┌─────────────┐
│ Intake │──────▶│ Parser │──────▶│ Scorer │
│ Agent │ │ Agent │ │ Agent │
└─────────────┘ └──────────────┘ └─────────────┘
│ │ │
│ ▼ ▼
│ ┌──────────────┐ ┌─────────────┐
└─────────────▶│ Validator │──────▶│ Ranker │
│ Agent │ │ Agent │
└──────────────┘ └─────────────┘
Why This Matters:
1. Self-Healing Retries
If the Parser agent hits a malformed PDF, it doesn't crash the pipeline. The Validator agent catches the error and triggers OCR fallback.
# Retry logic in Vectorhire's orchestration layer
async def parse_with_fallback(resume_file):
try:
return await parser_agent.extract(resume_file)
except ParseError as e:
logger.warning(f"Parse failed: {e}. Attempting OCR...")
return await ocr_agent.extract(resume_file)
except Exception as e:
return {"error": str(e), "status": "manual_review"}.
Proof in Production: Live Throughput Logs:
Client A: 1,247 screens | Avg cost: $1.88 | Uptime: 99.7%
Client B: 3,104 screens | Avg cost: $1.95 | Uptime: 99.9%
Client C: 612 screens | Avg cost: $1.82 | Uptime: 99.4%
🚀 Ready to Cut Your Screening Costs by 87%?
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