Our video consulting platform provides real-time audio/video streaming of data from one device to another using native WebRTC libraries. Hosted on a scalable AWS infrastructure the video platform offers a range of consultation solutions – text, audio and video chat. It supports all the latest desktop and mobile web browsers, a user-friendly and secure platform to connect over video calls.
The frontend video streaming component is built on Angular JS so that it can be integrated with any modern web application easily. It can be used as a standalone platform or integrated with existing systems for more effective calls.
The solution also uses intelligent bandwidth management to adjust audio/video and data transfer rates based on internet connection bandwidth of participants for better user experience. The solution is also capable of making customized settings based on different parameters for auto lock meeting rooms, password-protected rooms and screen sharing capabilities.
The applicability is proven in many domains, major ones being healthcare for doctor-patient consultation, e-learning, career counselling, legal and more. Main features are:
The primary objective of this project is to design and implement an event-driven backend system that automates the generation, validation, and delivery of healthcare-related EDI (Electronic Data Interchange) files, such as 834 (Eligibility and Enrollment), 837 (Claims), and 835 (Remittance Advice). These files are essential for secure, standardized, and compliant data exchange between healthcare providers, payers, and regulatory partners.
This system aims to:
This project delivers an integrated AI and analytics platform for the Foundation for Sickle Cell Disease Research (FSCDR). It connects ECW (eClinicalWorks) EHR data with advanced AI-based predictive models to identify high-risk patients, automate follow-ups, and streamline state grant reporting (CMO99, CMOAE Tasks 5–13).
The goal is to transform static EHR data into actionable insights — improving research visibility, compliance, and patient outcomes while cutting down manual reporting workloads. The solution supports predictive ER-risk modeling, AI-based outreach automation, and Power BI-driven compliance dashboards across FSCDR’s Centers of Excellence.
Medical Billing is a cloud-based charge capture solution designed for doctors to streamline patient list, accelerate billing, and optimise revenue capture by retrieving patient encounter details from EHR systems and leveraging Azure services. The solution aims to revolutionise healthcare charge capture by providing a user-friendly, efficient, and accurate solution that enhance revenue capture, improve operational efficiency and reduce administrative burdens for healthcare providers and organisations. By automating rounding list, the solution aims to facilitating streamlined patient assessment and service documentation during rounds, thereby enhancing overall workflow efficiency and billing accuracy.
Built on Microsoft Azure, system leverages Azure App Services for a scalable web application and Azure Kubernetes Service (AKS) for efficient micro services deployment.
Azure SQL Database and Azure Blob Storage securely manage patient records, financial transactions and medical documents, while Azure Key Vault ensures encryption and compliance with security standards.
Azure API Management (APIM) enables seamless integration with third-party services.
To automate claim processing and real-time tracking we have leveraged Azure Logic Apps and Azure Functions streamline data synchronisation and workflow execution.