AI-Powered Biomedical Image Analysis for Microscopy and Preclinical Assays

We provide advanced computational analysis of biomedical imaging data generated from microscopy-based assays, helping researchers and companies transform complex image datasets into quantitative and actionable biological insights.

Our expertise covers fluorescence microscopy, confocal imaging, 3D imaging, live-cell imaging, organoids, multicellular systems, and high-content screening applications. We develop tailored image analysis pipelines adapted to the specific needs of each project, from standard quantification tasks to fully customized AI-based solutions.

Services include:

• Automated image analysis for cellular and tissue-based assays.

• Cell, nucleus, organoid and tissue segmentation using state-of-the-art machine learning and deep learning approaches.

• Single-cell analysis and phenotypic profiling.

• Cell tracking and dynamic behavior analysis from time-lapse microscopy.

• Quantification of treatment responses in preclinical models.

• Analysis of cell-cell interactions and spatial organization.

• Biomarker discovery from imaging datasets.

• High-content image analysis and phenotypic screening workflows.

• Development of custom software tools and reproducible analysis pipelines.

• Integration of imaging data with transcriptomics, single-cell sequencing, spatial omics and other molecular datasets.

We work with academic groups, biotechnology companies and pharmaceutical partners seeking to extract maximum value from microscopy datasets generated in drug discovery, oncology, immunology, translational research and preclinical development.

Our solutions are designed to address challenging biological questions that cannot be solved through conventional image quantification approaches, enabling deeper characterization of cellular phenotypes, heterogeneity, mechanisms of action and treatment responses.