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.

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.

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.

We have extensive experience in automating mappings between medical coding and classification systems by computationally processing their semantic meaning, which can be extracted using NLP methodology or explicitly available from the classification model. Our successful applications include mappings made from ICD-10-PCS, LOINC, and ICD-O-3 systems for OHDSI OMOP Standardized Vocabularies.

The client works in the financial sector, helping businesses simplify reporting, budgeting, and forecasting. Their tools use real-time data and smart technology to create accurate reports, plan for the future, and test different scenarios. With features like multi-company and multi-currency support, easy-to-use dashboards, and seamless ERP integration, their solutions are flexible and scalable, making them ideal for businesses of all sizes looking to improve financial processes and support growth.