Blog - Page 3

Image recognition often looks impressive in demos. In real systems, its value shows up when algorithms support reliable decision-making within everyday operating conditions: speed, accuracy, privacy, and constrained infrastructure.  In delivery projects, these conditions often repeat. Companies solve similar tasks around on-device processing, real-time recognition, and data protection, and over time, these practical solutions shape how image recognition is designed and adopted across...

Ten years ago, EdTech platforms could get by and  perhaps even thrive on a centralized, monolithic learning management system and entertain learners without personalized UX. Back then, basic analytics and limited mobile support were enough to grow a customer base and stabilize the platform. But in 2026, the modern EdTech platform stack needs to be able to support personalization in...

According to the Pew Research Center, a quarter of U.S. teachers say that AI tools do more harm than good in K-12 education. But is it actually true, or is such a perception merely the result of not finding the right solutions to tackle the challenges of using AI in education? It’s a question we at CHI Software think about...

Facial recognition technology was a product of fiction for most people just about 20 years ago. However, it’s not new – the first solution was made around the 60s.  What started as a technology that recognized faces from newspapers and drawings evolved into today's greatest surveillance and personalization tool. At this point, facial recognition is widely implemented by different companies...

According to research, the global digital transformation market was valued at around USD 1,070 billion in 2024 and is projected to reach approximately USD 4,617 billion by 2030, with a strong compound annual growth rate of 28.5% from 2025 to 2030. This ongoing expansion reflects how businesses of all sizes are investing in modernization, cloud migration, automation, and other digital...

Legacy systems rarely fail overnight. More often, they continue running and gradually slow growth, increasing operational effort over time. The legacy modernization examples in this article show how business-critical systems reach a point where their structure no longer supports how companies work or scale. We’ve seen these outcomes in our own delivery. In one healthcare modernization project, automation and analytics...