Brevicor
Brevicor provides Canadian clinics with AI-driven automation that converts faxed referrals and paper questionnaires into structured intake data and pre-consult summaries. The platform extracts key referral details, flags missing information, and prepares clinicians before appointments while ensuring PHIPA-compliant data residency in Canada and seamless integration with existing EMRs such as Accuro, PS Suite, and OSCAR. This reduces manual re-entry work and lets staff focus more on patient care.
- Healthcare Technology
- Digital Health
- Artificial Intelligence
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
Canadian clinics receive referrals in highly varied formats—some via provincial eReferral tools, others as multi-page faxed PDFs, and a few as handwritten notes. Medical office assistants must print, read, and manually re-enter this information into EMRs before scheduling, leading to significant time loss, incomplete referrals, delays, and rescheduling.
Solution
Brevicor uses AI to read faxed referrals and paper questionnaires, converting them into structured intake data and pre-consult summaries. The platform centralizes referrals into a single queue, flags missing or incomplete information early, and prepares clinicians before the visit. It is designed to work alongside existing EMRs such as Accuro, PS Suite, and OSCAR rather than replacing them, and is built with Canadian data residency and PHIPA/PIPEDA-aligned safeguards. Specialty-specific workflows exist for sleep clinics, cardiology and diagnostics, and psychiatry and mental health, with intake fields mapped for HL7/FHIR alignment over time.
Target Audience
Primary customers are Canadian medical clinics and specialty practices—particularly sleep clinics, cardiology and diagnostics centers, and psychiatry and mental health teams—along with community sleep labs and virtual sleep programs that rely on fax-based referral intake.
Features
- AI-powered extraction of referral details from faxed documents, eReferral outputs, and handwritten notes into structured data
- Automated flagging of incomplete referrals and missing study information before the consult
- Pre-consult summary generation for clinicians covering sleep study requests, diagnostic intake details, and psychiatric assessments (PHQ-9, GAD-7, consent forms, intake histories)
- Centralized referral queue consolidating multiple incoming formats into a single digital workflow
- PHIPA/PIPEDA-aligned data handling with Canadian data residency
- Integration path designed to work with Accuro, PS Suite, OSCAR, and HL7/FHIR-aligned interoperability for downstream EMR and reporting workflows