Neutropy
AI healthcare platform automating patient scheduling, referrals, and insurance verification.

About Neutropy
Neutropy: AI Employees for Healthcare
Neutropy is an AI-powered healthcare platform designed to automate patient scheduling, reducing the process from days to minutes. By handling routine administrative tasks like reading referrals, calling patients, and updating electronic health records, the platform allows medical staff to focus on complex cases and patient care.
Key Features
- Automated Referral Processing: Reads GP referral letters, emails, and scanned PDFs while stripping personally identifiable information before processing.
- Multilingual Patient Outreach: Calls patients from the clinic's number and can automatically detect and switch between 12 or more languages mid-call.
- Direct EHR Integration: Writes scheduling data directly into major electronic health record systems like Epic, Oracle Health, and Athenahealth.
- Real-Time Insurance Verification: Naturally asks for and validates insurance providers and policy numbers during the scheduling call.
- Secure Identity Verification: Confirms patient identity before disclosing any medical details, safely ending calls if a household member answers.
- Smart Call Handling: Navigates real-world scenarios like voicemails, hang-ups, and dead air, continuously retrying until the correct person is reached.
- Seamless Human Escalation: Instantly warm-transfers calls to administrative staff for complex cases, failed verifications, or human requests.
Use Cases
- Healthcare facilities managing high volumes of routine patient scheduling and referrals
- Clinics seeking to reduce administrative backlogs and minimize missed appointments
- Medical practices serving diverse, multilingual patient populations
Getting Started
- Website: https://neutropy.ai/
Neutropy enables healthcare providers to streamline their administrative workflows by deploying AI agents that securely and efficiently manage routine patient scheduling, ensuring staff can prioritize meaningful patient interactions.