Case Study: CR Recruit

Clinical Research
AI-Powered ATS

Architect

Michael DeLaGuera

NuWorld Agency

100x Faster

Screening reduced from 5 hours to 3 minutes per candidate.

Gemini AI

Clinical-specific 4-dimension scoring rubric & vetting memos.

10 Workflows

Production n8n pipelines replacing manual spreadsheet work.

Project Phase

The 5-Hour Bottleneck

Clinical research recruiting requires deep domain expertise. Recruiters were drowning in 200+ resumes per role, manually checking for GCP, Therapeutic Areas, and CTMS proficiency.

The Manual Workflow

  • 01Manually scan 100+ PDF resumes for niche keywords (Veeva, Medidata, Oncology).
  • 02Hand-verify GCP certifications and FDA Phase I-IV experience.
  • 03Write 45-minute "Vetting Memos" explaining candidate fit to employers.
  • 04Sync spreadsheets across the team via email threads.

95% Efficiency Loss

Qualified candidates were slipping through because of manual screening fatigue.

Project Phase

A Three-Layer Architecture

I architected 'CR Recruit' as a modular ecosystem where the platform, the AI, and the automation work in concert.

Next.js 16React 19SupabaseTailwind v4

Layer 1: The Platform

A secure, role-based Talent Acquisition System managing candidates, employers, and job postings with enterprise-grade Auth.

Project Phase

The Gemini 'Consultative' Edge

How we automated the specific nuance that differentiated this system from generic agencies: the Vetting Memo.

4-Dimension Scoring Rubric

Clinical Experience92%

Years in field, Therapeutic area match

Regulatory Knowledge88%

GCP, ICH guidelines, FDA compliance

Therapeutic Expertise95%

Depth in specific disease state

Soft Skills75%

Communication signals, leadership

AI-Generated Vetting Memo

"Sarah Chen brings 7 years of oncology Phase III trial management with Medidata Rave proficiency, directly matching the site's CTMS requirement. Her experience managing 12-site multi-regional trials positions her well for the Study Director role overseeing 8 US sites. Notable strength: she has led 3 successful FDA inspections..."

Priority A (High Match)Drafted in 2.1s
Project Phase

The 10 Automation Engines

I deployed 10 production n8n workflows to manage the repetitive operational logic, decoupling automation from the core CR Recruit codebase.

Placement Onboarding

Fee calculation (20%) & automated tasking.

Employer Onboarding

Deduplication & branded welcome sequences.

Pipeline Automation

10-stage status transition logic.

Resume Intake

Gemini parsing & scoring on upload.

Google Sheets Sync

15-min real-time sync for visibility.

Guarantee Monitor

Expiry & payment alerts.

Weekly Report

Leadership HTML pipeline insights.

Employer Follow-Up

CRM re-engagement automation.

Candidate Reactivation

Stale candidate job-matching logic.

Bulk Import

CSV validation & profile generation.

Impact Summary

MetricBeforeAfter CR Recruit
Candidate Screening Time3-5 Hours2-3 Minutes
Vetting Memo Writing30-45 Minutes2-3 Minutes (Review only)
Resume Data EntryManual TypingAutomated (Gemini)
Pipeline VisibilityFragmented EmailsReal-time Dashboard
Nurture CampaignsNon-existentWeekly Automated Re-engagement

Strategic Takeaways

1

Niche AI beats Generic AI

The 4-dimension clinical rubric is why CR Recruit replaced manual experts, not just keyword filters.

2

n8n is the Operational Secret

Decoupling automation from the core app saved months of development and allows for instant logic pivots.

Build Your Agentic Future

I help niche businesses automate complex human workflows with Gemini Agents and n8n pipelines.

michael@nuworld.agency
linkedin.com/in/mdelaguera