The project aims to develop a web-based dynamic survey platform designed to capture consumer lifestyle preferences and habits. The survey will consist of four sections with approximately 20 questions and will incorporate conditional logic, ensuring that questions adapt based on user responses. If a respondent selects "yes" to a specific question, additional relevant questions will follow, while a "no" response will allow them to proceed to the next section. The survey should be easily accessible via email invitations or be completed directly by operators, ensuring flexibility in data collection.

The system should support data retrieval, reporting, and potential integration with marketing automation tools, making it a scalable and user-friendly solution for consumer engagement.

An AI-first, Gen Z–oriented fashion styling app enabling users to upload wardrobe items, receive personalized outfit suggestions using AI, and engage socially via outfit polls and feeds. The solution leverages Firebase’s scalable cloud backend and integrates OpenAI for prompt-based outfit generation. Users can manage a virtual closet, receive AI alerts on missing wardrobe items, and interact with a community through polls and comments. It also includes an admin panel for moderation, analytics, and subscription management. Monetization is driven through subscription tiers and integrated ads. The product is designed as a progressive MVP with clearly defined “must-have” and “nice-to-have” features to facilitate phased rollout. Post-launch, the client aims to validate market fit and scale with affiliate shopping and influencer integrations.

This Proof of Concept (POC) involves setting up a Mirth Connect integration to process HL7 messages for communication with the UAE government healthcare system. The workflow includes:

• Receiving a JSON request via an HTTP Listener.
• Converting JSON to HL7 format.
• Sending HL7 data to the UAE government endpoint.
• Handling real-time HL7 responses, converting them back to JSON, and sending the response to the HTTP requester.
• Implementing retry logic (configurable, e.g., 3 retries) in case the government server is unreachable.
• Ensuring nothing is hardcoded and using a config file for parameters like retry count.
• Supporting JWT Authentication for secure HTTP requests.
• Creating separate Mirth channels for each message type (ADT, ORM, etc.), starting with ADT messages.