Under Consideration
3Under consideration
Private Package Installation
User problem Users currently lack the ability to install internal or proprietary packages hosted on a private package index needed for their analysis. Without a way to connect securely to private repositories, users cannot utilize their organization's custom libraries or pre-built internal dependencies within the environment. What is it? This proposed feature is a secure integration capability that allows the Plotly Studio AI agent to connect to and authenticate with a private package index (such as an internal PyPI repository, JFrog Artifactory, or AWS CodeArtifact). It enables the AI agent to automatically fetch and install custom, non-public dependencies within a specific project. What does it allow users to do? Utilize proprietary libraries: Users can seamlessly integrate their organization’s private codebases, custom data models, and proprietary tools directly into their analysis. Maintain security and compliance: Users can safely pull packages from behind their corporate firewall or private registry without exposing sensitive internal code to the public domain. Automate enterprise workflows: The AI agent can automatically resolve and install internal dependencies on demand, ensuring that team projects remain aligned with corporate standards and private repository updates.
Plotly Studio in Dash Enterprise
User problem Many users operate within strict corporate environmentsm such as financial institutions, healthcare organizations, and government agencies, where local IT policies block the installation of desktop applications. Because these users lack administrative privileges to install software directly onto their work computers, they are unable to access and utilize the desktop version of Plotly Studio. What is it? This feature ports Plotly Studio into a web-based application accessible directly within the Dash Enterprise platform. Instead of requiring a local desktop installation, the tool is hosted centrally, allowing users to spin up and run individual, isolated instances of Plotly Studio entirely through their web browser. What does it allow users to do? Bypass Desktop Restrictions: Users can access the full capabilities of Plotly Studio from high-security networks without needing local administrative installation rights. Launch On-Demand Instances: Users can initialize a personal, cloud-hosted Studio environment with a single click directly inside Dash Enterprise. Streamline Workflows: Users can build, edit, and manage their data visualizations entirely in the cloud, keeping their data and tools centralized within the secure Dash Enterprise ecosystem.
Project Collaboration
User problem When working in Plotly Studio, team members often struggle to share critical project components, like data sources, artifacts, and active sessions, alongside relevant AI skills and team context. This lack of a centralized sharing mechanism slows down the onboarding process for new members, hinders the ability of teammates to collaborate and make necessary updates to each other's work, and creates a risk of teams operating without a unified, consistent context. What is it? This feature is a proposed sharing mechanism within Plotly Studio Cloud and DE designed to centralize and sync project components. By storing data sources, artifacts, sessions, and team context directly on the Plotly platform, it aims to create a unified space where team assets are easily accessible to authorized collaborators. What does it allow users to do? Centralize project assets: Users can store and access data sources, artifacts, and sessions in a single, platform-hosted location to keep all project elements in sync. Streamline team onboarding: Users can seamlessly pass down team context and required skills to new members, reducing the time it takes for them to get up to speed. Collaborate on shared work: Users can review, edit, and make updates to their teammates' active work and sessions, fostering a more agile and collaborative environment. Maintain data and context consistency: Users can ensure that the entire team is utilizing the exact same data sources and context, preventing version control issues and discrepancies across identical projects.
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