
At deepset, we collaborate with organizations of all sizes to help them build and deploy AI solutions that drive high-impact outcomes. As our customers move their AI projects into production, we've noticed a common theme: the need for enhanced security, risk mitigation, and precise access control. That's why we're excited to announce a major enhancement to our platform to address these requirements: enterprise-grade Role-Based Access Control (RBAC).
When CIOs and CTOs evaluate AI app development platforms, they must prioritize solutions that can seamlessly transition from experimentation to production while maintaining the highest security and compliance standards.
AI application development platforms, like the deepset AI Platform, empower organizations to rapidly test and deploy AI solutions using features such as app templates, pre-built components, and a visual builder. However, as these apps and agents move into production, it's crucial to ensure that the platform also provides robust security features, such as RBAC, to ensure access to sensitive data and workflows is carefully controlled.
deepset’s RBAC directly addresses these concerns by providing the necessary controls and flexibility to meet each organization's unique needs, allowing technical leaders to balance innovation and security effectively.
Our new RBAC enhancements include:
Refined Default Roles
We've introduced a more refined role hierarchy, with distinct roles at both the organization and workspace levels (segmented work areas by team, geo, project, production stages, etc). This allows platform admins to delegate responsibilities more effectively and lets builders to focus on developing and maintaining AI pipelines.
Custom Role Creation
Tailor workspace roles to match your teams' workflows. With granular permissions for essential platform features like Pipelines, Jobs, Feedback, Shareable Prototypes, and more, you can:
Workspace-Scoped Secrets & Integrations
Give your teams the ability to configure secrets (e.g., API keys for custom components or database connection strings) and integrations at the workspace level. Reduce dependencies across projects and enable teams to work autonomously while providing admins with the tools to enforce governance and access controls.
We're dedicated to evolving our platform to support enterprises as they advance their AI initiatives. This latest release marks an important milestone in our commitment to delivering a secure, flexible, and production-ready platform for our customers. Get all the details on RBAC in deepset AI Platform in our documentation.
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