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:
Cardiologists today face increasing administrative burden due to fragmented clinical data spread across EMRs, imaging systems, scanned PDFs, and external referrals. A single patient visit often requires reviewing dozens of documents, clinic notes, hospital summaries, imaging reports, labs, and medication histories, leading to inefficiencies, burnout, and reduced patient interaction time.
This project addresses a clear market gap: “A cardiology-focused AI assistant that retrieves, summarizes, and documents patient data with high accuracy, explainability, and seamless EMR integration.”
Cardiologists today face increasing administrative burden due to fragmented clinical data spread across EMRs, imaging systems, scanned PDFs, and external referrals. A single patient visit often requires reviewing dozens of documents, clinic notes, hospital summaries, imaging reports, labs, and medication histories, leading to inefficiencies, burnout, and reduced patient interaction time.
This project addresses a clear market gap: “A cardiology-focused AI assistant that retrieves, summarizes, and documents patient data with high accuracy, explainability, and seamless EMR integration.”
Objective of the Rental Automation Platform was to digitize and automate rent collection, lease management, and jurisdiction-based compliance workflows for landlords and tenants across multiple regions.
Traditional rental operations require manual tracking of payments, late notices, lease terms, and legal compliance — all of which vary by province/state and create operational risk and administrative overhead. The goal was to design a unified SaaS platform that embeds regulatory intelligence, automates rent workflows, and provides an audit-ready system for dispute or legal proceedings.
Platform is designed to:
The solution transforms rental operations into a compliant, data-driven, and highly automated ecosystem for both landlords and tenants.