Enterprise AI Mini-Platform Workflows for Faster LLM Deployment
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Solution Overview
Problem
Existing generative AI models for enterprises are labor-intensive, time-consuming, and expensive, requiring case-by-case implementation that lacks flexibility and ease of access, understanding, and updating.
Innovation Solution
A cloud-based generative AI operational environment with a mini-platform library and workflow function library, facilitated by an enterprise application integration component, enables automated model routing, orchestration, and secure data access, allowing customizable workflows for enterprise use cases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If generative AI models are implemented from scratch by an enterprise on a case-by-case basis, then the models can be customized for specific enterprise needs, but the implementation becomes labor-intensive, time-consuming, and expensive
Solution Approach 1:
The patent applies preliminary action by providing a framework with pre-configured components, templates, and workflows that are prepared in advance. This allows enterprises to leverage pre-built infrastructure rather than starting from scratch, significantly reducing implementation time and resources while maintaining customization capabilities through configurable parameters and modular components.
Solution Approach 2:
The framework implements universality by designing a multi-functional platform that can serve multiple enterprise needs through a single unified system. The framework provides reusable components, standardized interfaces, and configurable workflows that can be adapted to different use cases, eliminating the need for separate case-by-case implementations while maintaining adaptability to specific enterprise requirements.
2Adaptability or versatility
If traditional case-by-case implementation approaches are used, then models can be tailored to specific use cases, but the process lacks flexibility and ease of access, understanding, and updating
Solution Approach 1:
The patent applies segmentation by breaking down the generative AI implementation into modular, discrete components such as configurable workflows, reusable functions, and standardized interfaces. This segmentation enables enterprises to access, understand, and update specific parts of the system independently, improving ease of operation while maintaining the ability to tailor models to specific use cases through selective configuration of modules.
3Reliability
If manual implementation processes are used, then enterprises can have control over model development, but significant manual effort and operational costs are required
Solution Approach 1:
The framework implements self-service by providing automated workflows, self-configurable components, and intuitive interfaces that enable enterprises to implement and manage generative AI models with minimal manual intervention. The system automatically handles routine tasks such as model deployment, monitoring, and updates, reducing operational effort and costs while maintaining enterprise control through configurable parameters and management interfaces.
Data Source
AI summary
A generative AI framework for an enterprise may utilize a cloud-based generative AI operational environment to execute LLMs. A mini-platform library data store contains electronic records associated with a plurality of potential generative AI mini-platforms, and a workflow function library data store contains functions usable to customize managed workflows. A plurality of active enterprise mini-platforms may each be based on a potential generative AI mini-platform and have a customized managed workflow for an enterprise use case. An enterprise application integration component coupled to the cloud-based generative AI operational environment and the active enterprise mini-platforms facilitates model routing and orchestration to support the LLMs. The integration component may also interface between the cloud-based generative AI operational environment and the active enterprise mini-platforms to provide access to enterprise data that is processed via customized managed workflows.