Discover how our solutions have helped businesses overcome challenges and achieve success.
FurMed: Your Pet's Lifeline 🐾. Revolutionizing pet care, FurMed is more than an app; it's a commitment to your furry friend's well-being. Seamlessly manage pet profiles, locate vet clinics, and book services with love and care. Bridging the gap between pets and owners, FurMed is the heartfelt solution to everyday challenges.
React JS, Flutter, AWS, Node JS
Cogtix introduces TuneSpace, a user-friendly application that connects musicians and music enthusiasts with their dream studio spaces. TuneSpace simplifies the process of finding and booking music studios by the hour or day, catering to musicians, bands, producers, and creative minds looking for professional spaces to nurture their musical aspirations.
React JS, Flutter, AWS, Node JS
Cogtix Solutions undertook a challenging project to create FitReel, a hybrid mobile app for both Android and iOS platforms. FitReel was developed specifically for a fitness influencer client, aiming to provide users with a unique social networking experience combined with fitness tracking functionalities.
Next JS, Flutter, Node JS, Azure, Databricks
This case study is about a global financial company. Our client wanted to build a web-based SaaS(Software as a Service) custom software application to manage on-premise and cloud-based portfolios of their internal IT software applications. This can help the project managers and technical executives to govern, monitor, search, analyze dependencies, and standardize processes for different IT software applications across various business units. In addition, this helps software engineers and managers to document their application dependencies, application architecture, business capabilities, and deployment releases as well as search for information on other applications that they want to learn about.
Banking and Financial Services
React JS, AWS, Node JS
This case study is about a large Fortune 500 healthcare company. Our healthcare client needed to optimize the patients’ care as well as reduce accrued costs from later stages high-cost medical treatments of potential high-risk patients. For this project, the client aimed to develop various predictive systems that could generate a risk score to stratify the population in order to take relevant action for high-risk patients. Our client had historical demographics, medical claims, pharmacy claims, and clinical data such as doctor's notes and lab data of their patients. We first developed various analytical solutions to understand the data and obtain insights from it. We ran various experiments to obtain effective features and test various ML models on it. Ultimately, we developed an end-to-end data pipeline to clean the data, select and create effective features for the model, and built cost-effective classification and forecasting machine learning models using deep learning artificial neural networks. We developed models to predict 30 days patient readmission risk score, Congestive heart failure rate, Mortality rate, and Facility utilization rate.
Healthcare and Insurance Services
Python, AI/ML, Big Data, Azure, Databricks, Snowflake, Kafka, Spark