ZEISS arivis Hub is a centralized software platform designed for the management, processing, and analysis of large-scale microscopy image data. It enables efficient handling of high-volume datasets from diverse imaging modalities and supports automated, scalable, and AI-powered image analysis workflows. The platform provides secure user and permissions management, project sharing, and robust data organization through a hierarchical structure. ZEISS arivis Hub is compatible with image formats from various leading microscopes, regardless of file size, and can be deployed on-premises or in the cloud. It features a client/server architecture for fast, remote access and collaboration, and includes tools for metadata tagging, automated dataset uploads, and extensive image viewing. The system is suitable for a wide range of scientific and industrial applications, including biotechnology, cell biology, neuroscience, oncology, materials science, and geology.

Key Features

Centralized Data Management Organizes and secures all microscopy data in one place.

• Hierarchical data structure for efficient organization.
• Robust search and metadata tagging for easy retrieval.
• Secure user and group permissions management.

Scalable and Automated Image Analysis Handles large-scale and complex image analysis workflows.

• Automated, parallelized, and AI-powered image processing.
• Supports diverse applications and large datasets.

Collaboration and Accessibility Enables efficient teamwork and remote access.

• Project sharing and controlled access for multiple users.
• Client/server architecture for fast, remote data access.
• Web-based collaboration and annotation tools.

Flexible Deployment Adapts to different IT environments and user needs.

• Simple installation on cloud or on-premises infrastructure.
• Compatible with multiple image formats and microscope systems.

Integration and Extensibility Supports advanced workflows and interoperability.

• Integration with AI model training and analysis pipelines.
• Upload watcher for automated dataset ingestion.

Benefits

Efficiency in Large-Scale Research Accelerates time to reliable results in data-intensive environments.

• Streamlines data management and analysis for high-throughput labs.
• Reduces manual workload with automation and AI.

Enhanced Collaboration and Data Security Facilitates teamwork while maintaining data integrity.

• Secure, permission-based access and project sharing.
• Enables distributed teams to work on shared datasets.

Scalability and Flexibility Grows with research needs and adapts to various applications.

• Handles increasing data volumes and complexity.
• Deployable in cloud or on-premises to fit organizational requirements.