Ember provides an AI‑powered platform for healthcare staffing agencies that cleans, enriches, and updates candidate data in real time, enabling faster and more accurate job‑to‑candidate matching. The system automatically extracts availability, rates, locations, and certifications, syncing directly with ATSs and delivering instant job alerts, which has already enriched over 350 K candidate records and doubled submission efficiency without extra effort.
Funding
Funding not disclosed
Founders
Product
Problem
Healthcare staffing agencies often struggle with incomplete, outdated candidate data and manual matching processes, leading to low database engagement, high STOP reply rates, and missed placement opportunities.
Solution
Ember offers an AI-driven platform that cleans, enriches, and continuously updates candidate records within an agency’s ATS. Its healthcare‑specific models extract key attributes such as availability, rates, locations, and certifications, then write the enhanced data back to the ATS in real time. The system generates instant job‑to‑candidate alerts, enabling recruiters to submit candidates within a critical two‑hour window, which significantly improves offer rates. Integrated analytics highlight match quality and engagement metrics, helping agencies prioritize high‑potential candidates and reduce unproductive outreach. By automating data hygiene and matching, Ember allows recruiters to double their submissions without adding headcount.
Target Audience
Ember is designed for healthcare staffing agencies and recruitment teams that rely on ATS databases to source and place clinical professionals.
Features
- AI‑powered data enrichment that fills missing fields, standardizes formats, and validates certifications across 350K+ candidate records
- Real‑time ATS synchronization with automatic field write‑back, eliminating manual data entry
- Instant job alerts that surface the best candidate matches within minutes of a posting
- Match‑action analytics that track engagement, STOP reply rates, and submission effectiveness
- Healthcare‑specific AI models trained on industry data to understand candidate nuances better than generic tools