Domino Workflows Platform

Domino Workflows Platform is an innovative open-source solution designed to bridge the gap between ideas and implementation in data science and AI. It provides a user-friendly, no-code environment where professionals of all technical levels can create, edit, and monitor complex data and AI workflows. The platform emphasizes reusability, reproducibility, and collaboration, allowing users to easily share and leverage work across teams and the broader community. Built on top of Apache Airflow and optimized for Kubernetes, Domino offers a robust, scalable foundation for enterprise-grade data science operations.

The platform features an intuitive graphical interface for workflow creation, a standardized approach to building reusable functional pieces, rich real-time monitoring capabilities, and collaboration tools. It is powered by Apache Airflow, Kubernetes-native, and designed to bridge the gap between ideas and implementation for both technical and non-technical users.

Domino Workflows Platform supports a variety of use cases, including data science and machine learning, business process automation, research and development, ETL and data integration, and compliance and audit workflows. Its no-code interface makes advanced workflows accessible to non-technical users, while its open-source nature allows for customization and community contributions.

Highlights:

• Open-source, no-code platform for data science and AI workflows
• Built on Apache Airflow and optimized for Kubernetes
• Emphasizes reusability, reproducibility, and collaboration
• Intuitive graphical interface for workflow creation
• Supports a variety of use cases

Key Features:

• Visual Workflow Builder
• Reusable Functional Pieces
• Real-time Monitoring and Reporting
• Collaborative Workspaces
• Enterprise-grade Infrastructure

Benefits:

• No-code interface for non-technical users
• Customization and community contributions through open-source
• Scalability and reliability with enterprise-grade infrastructure
• Enhanced collaboration and reusability of components
• Support for complex data science and AI workflows

Use Cases:

• Data Science and Machine Learning
• Business Process Automation
• Research and Development
• ETL and Data Integration
• Compliance and Audit Workflows