ZEISS arivis Advanced Image Analysis

ZEISS arivis Advanced Image Analysis is a family of software products designed for researchers and scientists working with large, multi-dimensional microscopy datasets. The ecosystem addresses challenges related to growing data volumes, limited infrastructure, and storage silos by supporting multiple file formats, optimizing computing resources, and enabling AI-driven analysis without requiring coding skills. It is suited for applications across life sciences, biotech, pharma, neuroscience, organoid research, and industrial domains.

The ZEISS arivis ecosystem consists of three core products — arivis Pro, arivis Hub, and arivis Cloud — each targeting a distinct stage of the image analysis workflow, from visualization and pipeline creation through to batch processing, automation, and AI model training.

ZEISS arivis Pro — Visualization and Analysis

• Supports analysis across 2D, 3D, and 4D datasets with a flexible, customizable pipeline approach.
• Handles large datasets in real time, including immersive VR-based analysis environments.
• Compatible with pre-trained models such as Cellpose, as well as custom-trained AI models from arivis Cloud.
• Supports onboarding of new technologies through Python scripting.
• Provides tools for visualization tasks including cleared brain imaging and light sheet microscopy data.
• Formerly known as Vision4D and VisionVR.

ZEISS arivis Hub — Batch Processing and Automation

• Scales analysis pipelines created in arivis Pro through parallelized batch processing.
• Supports local, cloud, or hybrid computing environments to optimize resource use.
• Reduces project completion times through high-throughput scalability.
• Provides centralized, browser-based data access and user management for team collaboration.
• Streamlines data storage and information exchange across facilities.
• Integrates deep learning models into automated workflows.
• Formerly known as VisionHub.

ZEISS arivis Cloud — AI Model Training

• Provides a cloud-based platform for training custom deep learning models without prior AI or coding knowledge.
• Supports both instance (object-based) and semantic (pixel-based) segmentation tasks.
• Requires minimal image annotation to initiate model training.
• Trained models can be exported for local use and integrated into arivis Pro, ZEN, or ZEN core image analysis workflows.
• Enables significant throughput increases compared to manual analysis workflows.
• Supports reproducible results across different researchers and teams.
• Formerly known as APEER.

Key Platform Capabilities

• Supports diverse image sources and file formats across the full ecosystem.
• No coding required for core analysis and AI training tasks; Python scripting available for advanced customization.
• Enables reproducible results through standardized, automated pipelines.
• Applicable to neuron tracing, organoid growth analysis, Drosophila research, high content analysis, complex in vitro models (CIVMs), and polymer and soft material imaging.

Related Applications

• Automated neuron tracing and neuroscientific image analysis workflows.
• 3D image analysis for organoid research, including growth analysis beyond animal models.
• Drosophila model systems in life sciences.
• High content analysis for biotech and pharma.
• Scalable 3D imaging for complex in vitro models (CIVMs).
• Polymers and soft material imaging.

ZEISS arivis software is available under subscription-based institutional licenses and includes a Software Maintenance Agreement option. Documentation, application articles, and release updates are accessible through the ZEISS Knowledge Base. A Software Finder tool is available to help existing ZEISS microscope users identify compatible software for their systems. The platform is developed under ZEISS Microscopy's Cybersecurity and Data Privacy Governance Program, which also covers Responsible AI and Open Source Software governance.