Eluve provides medical AI solutions designed to integrate seamlessly into clinical workflows for healthcare providers. The platform offers an Ambient Scribe for automated documentation, a Clinical Copilot for real-time diagnostic insights, and Operations Intelligence for facility optimization. This technology lightens administrative burden, sharpens decision-making, and improves overall patient throughput and satisfaction.
Funding
Funding not disclosed
Founders
Product
Problem
Healthcare providers face significant administrative burdens due to the time-consuming nature of clinical documentation, billing code selection, and patient follow-up communication. These tasks contribute to burnout and detract from valuable patient care time.
Solution
Eluve offers an AI-powered ambient scribe that automates clinical paperwork by transcribing patient encounters and generating comprehensive medical notes. The platform analyzes conversations to recommend evidence-backed ICD-10, HCC, and CPT billing codes, improving reimbursement rates. Eluve also automates patient follow-ups by creating easy-to-understand clinical summaries and integrating with email systems to streamline communication. The system is designed to integrate seamlessly with existing Electronic Health Record (EHR) systems, ensuring a smooth workflow transition.
Target Audience
Eluve is designed for healthcare professionals, including physicians, nurses, and medical assistants, who seek to reduce administrative workload and improve efficiency in clinical documentation and patient communication.
Features
- Ambient AI-scribe that automatically generates clinical notes from patient visits
- Evidence-backed ICD-10, HCC, and CPT code recommendations to improve billing accuracy
- Automated generation of patient clinical summaries in simple language
- Email integration for streamlined patient follow-up communication
- Deep EHR integration customized to specific needs
- AI Safety Policy, HIPAA compliance, and encryption to ensure data security
- Continuous learning and optimization of AI models for improved performance