logo
Grow Smarter, Not Harder: Higher Yields with AI-driven Precision Farming

We teamed up with a Swiss agri-tech startup to build a platform that uses satellite images, radar data, and machine learning to give farmers a clear view of their crops. The system helps predict crop yields, spot weeds early, and estimate sugar content, giving farmers the info they need to boost their harvests and run their farms more efficiently.

Published: September 16, 2024
# Agriculture
# Computer Vision
# Data Science
# AI / ML
Tailoring Corporate EdTech with AI-Powered Personalized Learning

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.

Published: August 15, 2024
# EdTech / LMS
# Data Science
# NLP
# Big Data
# AI / ML
From Dublin to Frankfurt: EdTech Provider's AWS Migration into Compliance for Profit

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.

Published: May 21, 2024
# EdTech / LMS
# AI / ML
# DevOps
Transforming Complex Medical Data into Clinical Insights with Jackalope

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.

Published: April 29, 2024
# Healthcare
# Data Science
# AI / ML
All-Seeing EyeAI: a new era of space optimization and queue management

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.

Published: February 8, 2024
# Retail / E-commerce
# Computer Vision
Ticket Sales Prediction

In this case study, we developed a sophisticated ticket sales prediction system designed to evaluate the potential success of events using advanced data analytics. The system generates insights based on historical data, audience sentiment, and economic factors, providing actionable outputs.

Published: January 22, 2025
# Entertainment
# Data Science
# NLP
ML-Driven ECG Interpretation for Decision-Making

Cardiovascular diseases (CVDs) are a major global health concern, accounting for a significant number of deaths each year and being a leading cause of mortality worldwide. Accurate and timely diagnosis of CVDs is crucial for effective treatment and improved patient outcomes. The gold standard used for screening and diagnosing CVDs is Electrocardiography (ECG). However, accurately interpreting ECG results can be challenging for healthcare professionals. In this case study, we explored the implementation of Machine Learning (ML) for ECG recognition to enhance diagnostic accuracy and enable timely interventions.

Published: January 22, 2025
# Healthcare
# Data Science
# AI / ML
Patient Similarity Networks Development To Guide Clinical Decision-Making

A private research organization focused on evaluating the safety and effectiveness of medications. Their goal is to use advanced data analysis to support healthcare decisions and meet regulatory standards. For this project, they aimed to assess the safety of hydroxychloroquine, used alone or with azithromycin, for treating rheumatoid arthritis. The study focused on identifying short-term side effects and long-term risks, especially related to heart health and the use of multiple medications together. The client needed a data-driven approach to fill gaps in existing evidence by combining different clinical data sources, identifying patient groups with similar characteristics, and addressing factors that could affect treatment outcomes.

Published: January 21, 2025
# Healthcare
# Data Science
Automated Orchestration of Observational Research

Large data volumes are revolutionizing industries, including medical research. This influx of data enables observational studies that harness global statistical evidence. However, conducting such studies can be labor-intensive and prone to inconsistencies due to disconnected communication channels, like repositories, emails, forums, and chats. Moreover, adapting code to different environments during the execution phase can create unscalable and non-reusable analytical frameworks. In response, the OHDSI community is developing ARACHNE, an innovative platform designed to streamline observational research by fostering collaboration among life sciences, healthcare, academia, and organizations handling patient-level data.

Published: January 16, 2025
# Healthcare
# Big Data
Cohort Definition and Building

The OMOP CDM is widely recognized as the industry standard for observational health research. It provides a standardized data model that facilitates data integration and sharing across different sources, enabling researchers to conduct studies at scale. ATLAS is a central tool used for research within the OMOP CDM ecosystem, providing a user-friendly interface for querying the data model and creating visualizations. Building well-defined cohorts is a critical first step in conducting research using the OMOP CDM. By selecting and defining cohorts of patients with specific characteristics or conditions, researchers can ensure that their studies are focused and relevant, and can generate reliable evidence.

Published: January 16, 2025
# Healthcare
# Data Science