Healthcare & Clinical

AI-native intake and assessment for any specialty, any size.

Structured diagnostic assessments and patient intake forms — post-processed by AI to identify risk, generate clinical summaries, and accelerate care pathways. From private clinics to multi-site health systems.

Browse Apps

The challenge in healthcare data collection

✕Paper-based intake forms that don't adapt to patient condition
✕Standardized assessments (PHQ-9, GAD-7) completed manually and scored by hand
✕Clinical summaries written from scratch before every appointment
✕Risk factors buried in free-text responses — missed before the visit
✕No longitudinal tracking of patient outcomes across episodes
✕Inconsistent data quality across providers and locations

The structured assessment → AI post-processing workflow

Every patient interaction generates structured data that AI interprets — before a provider ever reviews it.

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STEP 01

Structured Intake

Patient completes adaptive, conditional intake form on any device — before arrival.

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STEP 02

AI Post-Processing

Responses auto-scored, risk factors flagged, and clinical summary generated.

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STEP 03

Provider Review

Clinician reviews AI-generated intelligence, not raw form data.

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STEP 04

Longitudinal Tracking

Outcomes tracked across sessions; patterns surfaced by AI over time.

Key use cases

MSK & Physiotherapy — Pre-Appointment Assessment

Patients complete functional assessments (NDI, DASH, Oswestry) before their appointment. AI scores responses and generates a SOAP note draft for the physiotherapist.

Conditional intake adapts to injury type and body region
Auto-scored NDI, DASH, Oswestry, and custom assessments
AI SOAP note draft ready before the appointment
Risk flags for high-complexity cases requiring senior clinician
Longitudinal outcome tracking across treatment episodes

Mental Health — Intake & Ongoing Monitoring

New clients complete mental health intake before their first session. PHQ-9, GAD-7, and PCL-5 are auto-scored. AI flags high-risk responses immediately.

Comprehensive mental health history with conditional branching
PHQ-9, GAD-7, PCL-5 auto-scored with severity interpretation
Crisis flag detection with immediate therapist notification
Session-by-session outcome tracking with trend visualization

Clinical Research — Participant Screening

Research coordinators screen participants against protocol criteria via AI-powered intake. Eligibility is scored automatically and protocol deviations are flagged.

Protocol-matched eligibility screening
AI eligibility scoring against inclusion/exclusion criteria
Longitudinal survey scheduling across study timeline
Research-grade data export (SPSS, CSV, REDCap)

Insurance & IME — Assessment Intake

Structured IME intake matched to case type. Medical history, functional capacity, and psychological assessments collected and AI-scored. Report generation accelerated.