Engineering intelligent systems at the intersection of biology, clinical medicine, and scalable information technology. Building the computational foundation for next-generation healthcare and biomedical research.
Four pillars of intelligent healthcare technology, unified under a single engineering framework.
Machine learning systems designed for clinical environments. Diagnostic support, predictive analytics, and decision assistance built on validated medical data and rigorous engineering standards.
Processing and analysis of biological data at scale. From genomic sequences to clinical records, transforming complex biomedical information into actionable intelligence.
End-to-end platforms that integrate AI capabilities into clinical workflows. Designed for healthcare professionals, built for reliability and regulatory awareness.
Robust backend systems and APIs powering medical AI applications. Secure, scalable, and designed with healthcare data requirements at the foundation.
Selected platforms and systems demonstrating the application of AI in healthcare and biotechnology.
AI-powered medical assistant platform for clinicians and individuals, supporting evidence-based decision-making, clinical workflows, and personal health record management.
An AI-driven evaluation system that simulates expert decision workflows to support major scientific research and venture project assessments with explainable and auditable results.
A retrieval-augmented AI system that transforms complex genetic reports into accessible, personalized health insights through natural language interaction.
Internal IT and data infrastructure modernization project focused on database systems, backend optimization, and reliable biomedical data management.
The integration of artificial intelligence into healthcare represents a fundamental shift in how medical decisions are made, research is conducted, and patient care is delivered. Our work focuses on building the technological foundation for this transformation.
AI systems that augment clinical judgment, reducing diagnostic uncertainty and supporting earlier detection of disease.
Intelligent systems that synthesize evidence and patient data to inform treatment decisions at the point of care.
Computational tools that analyze biomedical data at scale, accelerating discovery and enabling new research paradigms.
Infrastructure designed to bring AI capabilities to healthcare organizations of all sizes, from research labs to enterprise health systems.
Our technology stack is designed specifically for the requirements of healthcare and biomedical applications: secure data handling, reliable inference, and regulatory-aware architecture.
We collaborate with biotechnology companies, medical institutions, and research organizations to develop and deploy intelligent healthcare systems.