Back to Ventures// CASE STUDY SUMMARY

healthopenings.com: AI-Qualified Healthcare Recruitment Matrix

18k
Applications Prescreened
2,400+
Successful Placements

The Challenge

Hospitals faced a 40% applicant drop-off due to slow follow-ups, while candidates submitted unqualified resumes that clogged internal sourcing pipelines.

Our Approach & Solution

We implemented automated job scraping engines that import listings from hospital portals, and deployed a Claude-powered Twilio webhook agent that starts pre-screening chats on WhatsApp immediately after application submission.

Technical Deep Dive

Saves scraped postings with `status=pending` in the Supabase jobs registry. When candidates apply, a serverless trigger fires to initiate the screening conversation and update match scores.

Results & Outcomes

Hospital screening times dropped from 12 days to under 6 minutes. Sourcing yield increased by 2.6x with candidates highly praising the instant chat interface.

// System Specifications

Venture Role
Conversational Agent Engineering & Job Aggregator Scraper
Development Timeline
4 months
Deployment Domain
Technology Stack
Next.js 15PostgreSQLTwilio APIClaude 3.5 SonnetTailwind CSS