Our core competencies lie in the intersection between technology and healthcare. Our services portfolio includes projects in healthcare data harmonization and analysis, development of AI-powered mobile healthcare applications and cloud-based medical solutions.
We prove that advances in AI, big data and machine learning can provide new healthcare opportunities.
Digital Health management and data harmonizationWe integrate data from electronic health records, medical devices, and other sources to create a unified patient view. Our team analyzes, cleans, and harmonizes healthcare data, aligning it with standard medical models such as FHIR and OMOP CDM for consistency and reliability.
Ontology developmentBuilding ontologies from clinical data improves the recording of patient history, adherence to guidelines, and accountability of services. It also enables stronger systems and better data interaction in healthcare. As early contributors to the OHDSI community, we have developed multiple ontologies for diverse medical use cases.
Healthcare data scienceWe conduct observational research within the OMOP CDM ecosystem, from mapping source data to building concept sets and defining cohorts. Our expertise includes characterizing populations, estimating effects, and generating evidence. With domain knowledge in common data standards, medicine, and data science, we provide full lifecycle support to transform raw data into publishable research. 
Observation studies support and supervisionOur team supports observational studies across the full lifecycle, from converting healthcare data into OMOP CDM to generating evidence. We assist with study design, methodological improvements, and execution, ensuring reliable and reproducible research outcomes.
Medical data labelingIn healthcare AI, labeling assigns meaning to raw data such as images, text, or video. We have extensive experience segmenting and labeling anatomical structures in diverse medical images, including MRI and CT scans, enabling accurate training datasets for machine learning models.
AI/ML models for medical tasksOur CV and NLP experts build and refine algorithms for medical image analysis, claims processing, and clinical records. We deliver tailored, end-to-end solutions - from model training and fine-tuning to deploying complete computer-vision and NLP-powered systems for healthcare applications.
Medical data ETLWe specialize in designing and optimizing healthcare ETL pipelines, including real-time streaming. These processes provide insights into patient care, operational efficiency, and financial performance. Our data engineers ensure seamless integration and reliable management of critical healthcare workflows. Digital Health management and data harmonizationWe integrate data from electronic health records, medical devices, and other sources to create a unified patient view. Our team analyzes, cleans, and harmonizes healthcare data, aligning it with standard medical models such as FHIR and OMOP CDM for consistency and reliability. Ontology developmentBuilding ontologies from clinical data improves the recording of patient history, adherence to guidelines, and accountability of services. It also enables stronger systems and better data interaction in healthcare. As early contributors to the OHDSI community, we have developed multiple ontologies for diverse medical use cases. Healthcare data scienceWe conduct observational research within the OMOP CDM ecosystem, from mapping source data to building concept sets and defining cohorts. Our expertise includes characterizing populations, estimating effects, and generating evidence. With domain knowledge in common data standards, medicine, and data science, we provide full lifecycle support to transform raw data into publishable research. Observation studies support and supervisionOur team supports observational studies across the full lifecycle, from converting healthcare data into OMOP CDM to generating evidence. We assist with study design, methodological improvements, and execution, ensuring reliable and reproducible research outcomes. Medical data labelingIn healthcare AI, labeling assigns meaning to raw data such as images, text, or video. We have extensive experience segmenting and labeling anatomical structures in diverse medical images, including MRI and CT scans, enabling accurate training datasets for machine learning models. AI/ML models for medical tasksOur CV and NLP experts build and refine algorithms for medical image analysis, claims processing, and clinical records. We deliver tailored, end-to-end solutions - from model training and fine-tuning to deploying complete computer-vision and NLP-powered systems for healthcare applications. Medical data ETLWe specialize in designing and optimizing healthcare ETL pipelines, including real-time streaming. These processes provide insights into patient care, operational efficiency, and financial performance. Our data engineers ensure seamless integration and reliable management of critical healthcare workflows.
