Case studies

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.

Explore how an EdTech company boosted its profitability and expanded its market by moving its AWS infrastructure from Ireland to Germany. This shift complied with strict German data protection laws and improved system performance while cutting operational costs, creating new opportunities in Europe.

Jackalope transforms complex medical data into OMOP CDM and SNOMED Clinical Terms (CT) standardized formats. This enables healthcare providers, practitioners, and scientists to effectively use real-world medical data for research and delivering enhanced patient care.

EyeAI 👁️ is a SciForce product, transforming your existing cameras into a smart system for optimizing space and managing queues. Get real-time insights into visitor behavior for better space use and personalized service in retail, healthcare, HoReCa, and public safety—no new hardware needed.

For a video processing platform handling high upload volumes, we developed an automated, scalable pipeline using Python, AWS ECS, and Fargate. This smart solution dynamically scales, reduces resource waste, and enables seamless, hands-free video processing across formats—empowering the client to meet demand peaks effortlessly.

The language learning platform adapts to each user’s progress, providing customized exercises and challenges. Gamification features like leaderboards, badges, and progress tracking make learning more engaging and enjoyable. From basic vocabulary to complex scripts like Mandarin and Arabic, the platform makes language learning both fun and effective.

Our client, a technology company managing large data centers, faced recurring pump failures in their cooling systems, causing costly downtimes. By deploying an advanced anomaly detection system, we identified critical sensor patterns that allowed the maintenance team to address issues before they escalated. This led to a 30% reduction in false alarms and a 25% decrease in unplanned downtime.

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.