AI-Driven Medical Documentation Solution
Budget: ₹600 – ₹800 INR
Project Description:
Apply only if you have fully experience this technology stack:
We are developing an AI-driven medical documentation platform that uses Cursor AI and Google Gemini/OpenAI for real-time transcription, SOAP note generation, and clinical documentation automation.
The project aims to assist healthcare professionals in efficiently generating structured, compliant medical records using FHIR (HL7) standards and secure PostgreSQL data storage.
Technology Stack:
Frontend:
React 18+ with TypeScript
Vite for fast builds
Tailwind CSS / shadcn/ui / Radix UI for UI and theming
TanStack Query (React Query) for data fetching
React Hook Form + Zod for form validation
Lucide Icons, Recharts, date-fns, Sonner for UI enhancements
Backend:
Node.js / Express.js
Supabase (PostgreSQL) for authentication and database
REST API / FHIR-compliant endpoints
RBAC / MFA / Audit Logging (HIPAA & GDPR readiness)
AI & NLP:
Cursor AI integration for context-aware code and AI orchestration
Google Gemini / OpenAI / Azure OpenAI APIs for transcription and SOAP generation
Browser Speech API for real-time speech recognition
Custom AI prompt system (template-based, versioned)
Database:
PostgreSQL (via Supabase)
FHIR resources (Patient, Encounter, Observation, etc.)
Clinical terminologies: SNOMED CT, ICD-10/11, LOINC, RxNorm (planned)
Project Goals:
Build scalable, modular, and secure AI-assisted medical documentation system
Implement real-time speech-to-text and automated SOAP note generation
Ensure compliance with HIPAA, GDPR, and FHIR R4 standards
Create an intuitive, responsive web interface for clinicians
Deliverables:
Full-stack application (frontend + backend + database)
Working AI integration with Cursor AI and Gemini/OpenAI
Deployed environment with Supabase
Documentation for setup, APIs, and architecture
Apply only if you have fully experience this technology stack:
We are developing an AI-driven medical documentation platform that uses Cursor AI and Google Gemini/OpenAI for real-time transcription, SOAP note generation, and clinical documentation automation.
The project aims to assist healthcare professionals in efficiently generating structured, compliant medical records using FHIR (HL7) standards and secure PostgreSQL data storage.
Technology Stack:
Frontend:
React 18+ with TypeScript
Vite for fast builds
Tailwind CSS / shadcn/ui / Radix UI for UI and theming
TanStack Query (React Query) for data fetching
React Hook Form + Zod for form validation
Lucide Icons, Recharts, date-fns, Sonner for UI enhancements
Backend:
Node.js / Express.js
Supabase (PostgreSQL) for authentication and database
REST API / FHIR-compliant endpoints
RBAC / MFA / Audit Logging (HIPAA & GDPR readiness)
AI & NLP:
Cursor AI integration for context-aware code and AI orchestration
Google Gemini / OpenAI / Azure OpenAI APIs for transcription and SOAP generation
Browser Speech API for real-time speech recognition
Custom AI prompt system (template-based, versioned)
Database:
PostgreSQL (via Supabase)
FHIR resources (Patient, Encounter, Observation, etc.)
Clinical terminologies: SNOMED CT, ICD-10/11, LOINC, RxNorm (planned)
Project Goals:
Build scalable, modular, and secure AI-assisted medical documentation system
Implement real-time speech-to-text and automated SOAP note generation
Ensure compliance with HIPAA, GDPR, and FHIR R4 standards
Create an intuitive, responsive web interface for clinicians
Deliverables:
Full-stack application (frontend + backend + database)
Working AI integration with Cursor AI and Gemini/OpenAI
Deployed environment with Supabase
Documentation for setup, APIs, and architecture