AI-powered clinical intake and triage support for faster care decisions.
DiagnosAI helps patients and healthcare providers move from symptoms to structured medical guidance through adaptive intake, risk assessment, and care navigation.
Symptom Intake
Risk Assessment
Care Guidance
Delayed and inconsistent triage is putting patients at risk.
Emergency demand is rising, but triage is still manual, crowded, and inconsistent. Delays and under-triage create preventable risk at the front door of care.
16.1M
ED visits in Canada last year
7.7%
of patients left before seeing a physician
1 in 10
admitted patients waited 36+ hours for a bed
Under-triage costs lives
In an Ontario trauma study of 11,398 severely injured patients, 4% died before transfer — accounting for 22% of all deaths in the cohort.
A problem far beyond Canada
The U.S. sees roughly 140M ED visits every year, and triage-related deaths still aren't formally tracked nationally in either country.
Incomplete patient information
Clinics and EDs receive fragmented symptom histories at intake, leaving clinicians to make triage decisions without the full picture.
Manual, inconsistent triage
Prioritization still runs on manual review. As volumes rise, that slows everyone down and increases waiting time across the board.
Missed urgency, rising risk
When early warning signs go unnoticed or escalation is delayed, patient risk climbs before care has even begun.
Delays, under-triage, and overcrowding create preventable risk at the front door of care.
Sources: CIHI (2026), ICES / JAMA Surgery trauma under-triage study, CDC/NAMCS
AI-powered clinical triage, before the clinician sees the patient.
DiagnosAI performs intelligent patient intake and triage ahead of the visit, delivering clarity, prioritization, and efficiency to everyone involved in care.
Intelligent Symptom Intake
Patients describe symptoms in natural language, and the AI asks the right follow-up questions to build a complete picture.
Risk & Urgency Assessment
The system evaluates severity, detects red flags, and assigns an urgency level before the patient reaches the clinician.
Clinical Summary Generation
Creates a structured, standardized summary of symptoms, history, and relevant findings for the care team.
Actionable Recommendations
Suggests the appropriate specialty, tests if needed, and clear next steps for the patient's care.
Provider-Ready Insights
Delivers clear, structured insights directly to hospital systems and care teams, ready for review.
Who Benefits
Patients
Faster care, shorter waits, and a better experience from the very first symptom.
Clinicians
Complete information upfront, better prioritization, and more time for patient care.
Hospitals
Improved efficiency, optimized resources, and better clinical outcomes across departments.
DiagnosAI turns unstructured conversations into actionable clinical insights, so hospitals can focus on what matters most: patient care.
Starting with respiratory health.
DiagnosAI's first MVP focuses on respiratory symptoms — a high-frequency use case where structured intake, red-flag detection, and timely guidance can make a meaningful difference.
Respiratory care is among the most common reasons patients seek medical attention. Early structured triage helps clinicians prioritize and helps patients understand when to act.
Clinical safety first. DiagnosAI does not provide final diagnosis or replace clinical judgment. It supports safer and more structured pre-consultation assessment.
Focus area
Respiratory Symptoms
Expanding to more clinical areas over time
How DiagnosAI works
Symptoms → Adaptive Intake → Risk Assessment → Clinical Summary → Care Guidance
Patient enters symptoms
The patient describes what they are experiencing in natural language.
Adaptive follow-up questions
DiagnosAI asks targeted follow-up questions based on the initial input to build a complete clinical picture.
Optional health inputs added
Vitals, respiratory sounds, or other available health data can be attached to improve assessment accuracy.
Urgency and red-flag assessment
The system evaluates the collected information, identifies warning signs, and determines urgency level.
Clinician-ready summary generated
A structured clinical summary is produced, ready for the healthcare provider before or during consultation.
Patient guided to next step
The patient receives clear, appropriate guidance: self-care, testing, consultation, or urgent escalation.
Patient enters symptoms
The patient describes what they are experiencing in natural language.
Adaptive follow-up questions
DiagnosAI asks targeted follow-up questions based on the initial input to build a complete clinical picture.
Optional health inputs added
Vitals, respiratory sounds, or other available health data can be attached to improve assessment accuracy.
Urgency and red-flag assessment
The system evaluates the collected information, identifies warning signs, and determines urgency level.
Clinician-ready summary generated
A structured clinical summary is produced, ready for the healthcare provider before or during consultation.
Patient guided to next step
The patient receives clear, appropriate guidance: self-care, testing, consultation, or urgent escalation.
Built for clinics, telehealth providers, and care networks.
DiagnosAI helps healthcare teams collect structured patient information before consultation, reduce repetitive intake burden, identify urgent cases earlier, and improve care navigation.
Key Benefits
A smarter intake experience before the visit.
See how DiagnosAI structures a patient interaction and produces a clinician-ready output.
Patient Input
“I have had a cough and breathing difficulty for three days.”
DiagnosAI Follow-Up
“Do you have chest pain, fever, wheezing, shortness of breath at rest, or low oxygen levels?”
Structured Output
Clinical Summary
Persistent cough with breathing discomfort, no severe red flags reported. Follow-up consultation recommended.
Demo only. This example is for demonstration purposes. DiagnosAI is intended to support intake and triage workflows — not replace professional medical advice, diagnosis, or treatment.
Our vision
DiagnosAI aims to become a scalable AI-powered diagnosis and care navigation platform that helps people move from symptoms to the right medical action faster.
We are starting with focused clinical use cases and expanding toward a broader multi-agent medical reasoning system for accessible, structured, and timely healthcare support.
Focused first
Starting with high-impact clinical use cases — respiratory intake, structured triage, and red-flag detection — before expanding scope.
Multi-agent reasoning
Building toward a broader platform with multiple specialized AI agents that collaborate across clinical domains for richer medical reasoning.
Accessible at scale
Making structured, timely healthcare guidance accessible to patients and providers globally, regardless of geography or resource constraints.
Interested in piloting DiagnosAI?
We are looking to collaborate with clinicians, clinics, telehealth providers, healthcare innovation partners, and early pilot sites. Let's build the future of clinical intake together.