IKOSA is a next-gen bioimage analysis platform that replaces slow, subjective manual workflows with fast, reproducible and trustworthy AI. It combines intuitive multi-user image data management with tools to train, evaluate, and deploy your own deep-learning models, plus ready-to-use analysis apps and visualization. For advanced needs, our AI experts co-develop and integrate visual computing solutions to cut turnaround times and bottlenecks.
With IKOSA platform features at hand you have the tools to extract insightful multidimensional information from your image data. Our platform enables you to analyze images across various microscope sources and imaging modalities while you keep full control of your AI-driven analysis workflow.
Work simultaneously, collaborate in the process, share applications and projects, view each other's image analysis visualizations. All this is possible within an IKOSA organization. Maintain access control with a transparent role and permission concept.
From data management to AI-driven analysis and data visualization, we've got you and your team covered with a comprehensive feature set.
Achieve the best performance for your application with visualizations and performance metrics in your training report. It allows you to identify where your AI model performs well, and where it needs improvement. Easily compare models side-by-side across training iterations.
The publicly available IKOSA Knowledge Base is a collection of educational materials that will help you master any bioimage analysis task. Get access to helpful learning materials and tutorials on the workings of IKOSA. Read up details on the output features of IKOSA image analysis applications.
IKOSA AI applied to phase-contrast microscopy images predicts lumen formation, improving consistency of organ-on-chip studies as alternative to animal testing in drug discovery in neuroscience.
Applying IKOSA AI to 2D/3D images of micro-physiological systems, organoids, microtissues and cell cultures enables quantitative assessment of morphology and culture quality for robust quality control. This strengthens assay reproducibility and increases confidence in drug-response readouts.