Case studies

The client is a healthcare company focused on medical imaging and diagnostics, working to improve the diagnosis of lung diseases like tuberculosis and COVID-19. They wanted to create an AI-based algorithm that could detect abnormal changes in chest X-rays and automatically prioritize the most urgent cases. It helps to make the diagnostic process faster and more accurate by identifying abnormalities and highlighting critical cases. It reduces the workload for radiologists and pulmonologists by automating routine tasks, so they can focus on more complex cases. By solving issues like delayed diagnoses and heavy workloads, the solution ensures patients with serious conditions get quicker and more reliable care.

Our client in the corporate EdTech sector developed a platform that aggregates business courses for easy access and management. They sought an automated system to categorize courses into areas like marketing, finance, and HR, and to recommend personalized learning paths based on each employee's role and career goals. Read on to learn about our ML solution that transforms course categorization and tailors personalized recommendations.

Our solution uses advanced Natural Language Processing (NLP) and Machine Learning (ML) to automate the extraction of detailed specifications and measurements from complex product spec sheets.

Transform your legal document management with our advanced AI system. Built to streamline contract analysis, this solution cuts down on manual work and boosts accuracy, making the process of handling legal contracts more efficient and precise.

In the recent decade, as people have moved away from desktops to mobile devices, their consumption patterns have undergone significant transformation. One of such changes is the boost of video consumption from smartphones, which prompted mobile video advertising. Today, by creating a video tailored for mobile devices and the behavior of mobile users, advertisers can now achieve successful performance. At the same time, though growing in popularity, videos become shorter: in 2016, the average video length was 13.14 minutes, in 2017 6.07 minutes, and in 2018 it shrank to 4.07 minutes. So how is it possible to cut videos maintaining the content significance, and adjusting it to the viewer’s preferences? The answer seems obvious: you need to make your videos shorter and more content-intensive. But the reality is not that straightforward: each platform requires its format, length, and size, so you end up creating tons of video materials.

We designed an ML-powered system for personified lab test results. It boosts the efficiency of physician office laboratories (POLs) and increases the speed of the medical service delivery system. Moreover, the system that we created became a part of a broader telemedical patient care delivery system. Read on to find out how we deal with challenges like this one.