An AI-powered Quality Assurance (QA) tool developed to enhance the customer support experience by automatically analysing customer-agent conversations( both actual human agents as well as agentic bots too). It identifies policy violations, customer sentiment, and agent performance insights in real-time. Platform integrates with CRMs and uses machine learning (ML) and natural language processing (NLP) to offer actionable insights for businesses seeking to improve service quality and operational efficiency. This will help organisations to streamline support analysis, improve agent training, and monitor customer satisfaction metrics. 

Dental EHR is a comprehensive electronic health record system designed to enhance the efficiency and accuracy of dental practice management. This platform streamlines patient scheduling, appointment tracking, treatment documentation, and communication, ensuring a seamless experience for both providers and patients.
It provides real-time patient flow tracking, enabling dental staff to monitor which patients have arrived, their appointment details, and their assigned provider or treatment room. The system allows easy modifications to room assignments and provider scheduling, ensuring better patient care coordination. Flexible appointment scheduling is integrated, allowing clinics to create, edit, and manage bookings in daily, weekly, and monthly views while reducing no-shows through automated appointment reminders.
For documentation and communication, the system offers custom letter generation, which automatically fills referral or patient letters with relevant details from stored records. Comprehensive patient information management ensures easy access to patient history, treatment records, and previous interactions, all displayed in an intuitive format. Additionally, secure authentication is implemented, allowing seamless transitions between desktop and web applications while maintaining data privacy and security compliance.

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.