AI Model Deployment Gateway for Secure On-Premises Provisioning
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Solution Overview
Problem
Users lack knowledge on how to utilize generative AI technologies and face new security concerns when deploying AI models, especially in on-premises environments, requiring a user-friendly platform for secure deployment and resource management.
Innovation Solution
A platform that orchestrates the deployment of AI models in virtual or cloud environments, manages resource allocation, performs DLP scanning, and obfuscates sensitive data, simplifying the deployment process and enhancing security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users directly deploy AI models in on-premises environments, then security control is improved, but user knowledge requirements and deployment complexity increase
Solution Approach 1:
The patent introduces an on-premises gateway as an intermediary component that mediates between users and the AI model deployment infrastructure. The gateway provides user-friendly interfaces and automated resource orchestration, allowing users to deploy models without needing deep technical knowledge while maintaining security through centralized control and monitoring capabilities.
2Ease of operation
If cloud resources are used for AI model deployment, then ease of deployment is improved, but data security and organizational control worsen
Solution Approach 1:
The patent implements local quality by deploying AI models within the organization's own infrastructure through the on-premises gateway, rather than using centralized cloud resources. This allows data to remain within organizational boundaries while still providing cloud-like ease of deployment through automated resource management and orchestration capabilities built into the gateway.
3Productivity
If comprehensive resource orchestration is implemented, then deployment efficiency is improved, but system complexity increases
Solution Approach 1:
The patent implements self-service through automated resource orchestration within the on-premises gateway. The system automatically manages computing resources, allocates hardware acceleration capabilities, and coordinates model deployment without requiring manual intervention. This automation improves deployment efficiency while hiding the underlying system complexity from users through standardized interfaces and workflows.
Data Source
AI summary
A user-friendly platform provides a simplified procedure for end users to deploy models that utilize generative AI to perform tasks (hereinafter simply “AI model”) in a deployment environment (e.g. in a data center). Upon selection of an AI model to be deployed, the platform orchestrates deployment and allocation of resources that satisfy hardware requirements of the AI model. The platform includes an agent that communicates with infrastructure of the cloud provider or virtualization platform that manages deployed resources tracks allocation of hardware resources to virtual/cloud resources running on the deployment environment. The platform handles deployment of resources for deployment of the AI model “behind-the-scenes” from the user's perspective based on the monitored availability of hardware resources. For added security, the platform performs DLP scanning of data uploaded to the platform for input to an AI model that has been deployed.