Statistical consulting and advisory
Statistical support across all stages of clinical and med‑tech projects. Study design, data strategies, and statistical analyses. Development and review of statistical models and AI solutions. Evaluation of clinical evidence and regulatory compliance. Safe and effective integration of analytics into everyday clinical practice.
Digital platforms and analytical solutions
Development of patient‑stratification systems and risk calculators. Analytics tools designed for clinical decision support. Custom platforms for day‑to‑day use in practice, tailored to an organization’s aims.
In‑depth data insights
Identifying key, often hidden patterns in complex clinical data. Data mining and advanced analytical workflows. Analyses of real‑world data (e.g., patients’ historical data, electronic health records). Development of predictive models, prognostic tools, and risk profiles. Support for diagnosis, prognosis, and therapeutic decision‑making.
Health Technology Assessment (HTA)
Support for tech companies in HTA regulatory processes. Evaluation frameworks designed to support registration and certification pathways. Frameworks supporting registration and certification of AI‑enabled technologies/devices.
Survey design and analysis
We develop high‑quality surveys and turn collected responses into reliable, actionable insights. Our work spans questionnaire design, data preparation, and interpretation for clinical and research applications.
Data engineering and harmonization
Integration and standardization of data from diverse sources and tools. Construction of coherent, analysis‑ready data frameworks. Harmonization of text, images, and structured data into unified formats. Full data‑processing pipelines including cleaning and quality control.
Care‑quality monitoring systems
Solutions that continuously track the quality and safety of care. Systems for real‑time monitoring of surgical performance, assessing learning curves, and overseeing clinical outcomes. Monitoring of complications, medical failures, and process deviations for audit aims. Risk‑adjusted performance indicators, automated alerts, and benchmark comparisons across care units.
AI performance monitoring
Real‑time monitoring systems for tracking AI/device performance. Detection of systematic drifts, outliers and automation bias. Stability and safety assessment of AI models and connected medical devices.