The Data Science & AI Workbench by Anaconda stands as a pivotal platform for data science and AI teams aiming to innovate and expedite model deployment. This platform ensures that all developments adhere to stringent security and governance requirements, providing a secure environment for AI project management. With features like one-click deployment, teams can significantly reduce the time from development to deployment, transitioning from weeks to mere minutes. This efficiency is crucial for gathering stakeholder feedback and integrating it into the model, ensuring it's production-ready from the start.
Collaboration is at the heart of the Data Science & AI Workbench, offering cloud-based collaboration tools that connect users to community innovation. This fosters an environment where teams can train at their own pace, leveraging open-source libraries from Anaconda’s Premium Repository. The repository offers access to thousands of packages and libraries, with policy filters in place to eliminate vulnerabilities and non-compliant packages, ensuring a secure and efficient workflow.
Training and deploying AI projects are streamlined on this platform, with a scheduler that specifies data updates for training or retraining existing models. This feature, combined with the ability to develop and register models faster, collaborate by project, and deploy in one click, minimizes the time to value for AI projects. Additionally, the platform offers disaster recovery capabilities, ensuring data and environments can be restored in the event of a disaster or outage, such as data deletion or hardware failures.
GPU-enabled workflows provide the flexibility to leverage computational power, with the capability to provision GPUs for sessions, deployments, and jobs. This ensures cost control and efficient resource management, crucial for handling complex AI models. The AI Assistant feature offers support in overcoming coding challenges, providing relevant answers within the notebook environment, enhancing productivity and learning.
Administration and governance are simplified with Single Sign-On (SSO), Role-Based User Access Controls (RBAC), and Prometheus integration for compliance, efficient log gathering, insights, and resource management. Open-source MLOps capabilities allow for the registration and definition of experiment model versions, ensuring the proper models are deployed to production. The platform's built-in security across the open-source stack empowers practitioners with access to open-source tools and packages across coding languages, stopping risks without hindering workflows.
Visibility and governance are enhanced with controls over account provisioning and access for security teams, alongside commercial support that provides enterprise-grade expertise in open-source security and compliance. The Data Science & AI Workbench is a testament to Anaconda's commitment to providing a secure, efficient, and collaborative environment for AI and data science projects, enabling teams to innovate and deploy with confidence.
