Intake Copilot
Bilingual intake flows for symptoms, history, medications, allergies, and visit goals.
- Arabic and English patient responses
- Missing information prompts
- Clinic-specific intake templates
Product suite for private pilots
One workspace for intake, documents, and doctor-reviewed notes.
TabibAI is designed as a clinical workflow layer for clinics and telemedicine teams: collect patient context, organize uploaded files, draft physician-ready notes, and keep clinicians in control.
Draft-onlyAI output is reviewed by licensed clinicians.
Arabic + EnglishBuilt around bilingual clinic workflows.
Cloud-readyDesigned for secure storage, audit logs, and inference workloads.
tabibai.dev / products
Clinical intake
Structured patient history collection before the clinician enters the visit.
Document intelligence
Organizes lab reports, PDFs, discharge notes, and patient-uploaded files into reviewable summaries.
Physician-ready notes
Creates draft notes, checklists, and missing-information prompts for professional review.
Products
A focused suite instead of a generic chatbot. Each module supports a real clinic workflow and keeps final medical judgment with the clinician.
Document Review
Turns uploaded medical documents into source-aware summaries for faster human review.
- Lab and report organization
- Document timeline extraction
- Draft-only summary output
Doctor Notes
Prepares structured notes for clinicians to edit, approve, or reject before they enter the record.
- SOAP-style draft notes
- Review checklist
- Audit-friendly status tracking
Team Workspace
Central queue for intake sessions, uploaded files, draft notes, and review status.
- Patient queue demo
- Role-based workflow direction
- Founder and clinic pilot view
Safety Layer
Clear boundaries for medical AI: no diagnosis, no prescribing, and no autonomous care decisions.
- Clinician supervision copy
- Draft labels on outputs
- Medical disclaimer built in
Cloud Foundation
Architecture direction for AWS-hosted inference, document processing, secure storage, and audit logs.
- Compute and inference workloads
- Object storage for files
- Logging and environment separation
Workflow
The product story AWS reviewers should see: a real cloud-backed workflow with responsible healthcare positioning.
Collect intake
Patients submit history and documents before the visit through controlled forms.
Organize evidence
Reports and free-text answers are summarized into clinician-reviewable context.
Draft documentation
The system prepares draft notes and missing-information prompts.
Clinician approves
A professional reviews, edits, and finalizes; TabibAI does not replace judgment.