Rules Engine for Contextual AI Request Routing Under Enterprise Policies
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Solution Overview
Problem
Current systems lack the capability to intelligently route user requests to the appropriate AI endpoint based on the content and context of the request, leading to inefficiencies and potential violations of data access protocols due to misallocation of enterprise resources and unauthorized access to sensitive information.
Innovation Solution
A rules engine that integrates multiple AI platforms and models, applying management rules and user preferences, along with contextual analysis, to determine the most suitable AI endpoint for a request, ensuring compliance with enterprise policies and user intent, and includes a specialized routing AI Model for nuanced evaluations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users can access multiple AI endpoints (personal and managed) through a unified interface, then user convenience and accessibility are improved, but resource misallocation and unauthorized data access occur
Solution Approach 1:
The patent introduces a rules engine as an intermediary component between the user interface and AI endpoints. This rules engine evaluates user requests against predefined management rules and contextual factors, determining the appropriate AI endpoint for each request. The rules engine acts as a mediator that enables unified access while preventing unauthorized data exposure by routing personal requests to personal endpoints and enterprise requests to managed endpoints based on contextual analysis.
2Productivity
If enterprise resources are made accessible to multiple users, then resource utilization efficiency is improved, but unauthorized access to sensitive information and misallocation occur
Solution Approach 1:
The patent implements dynamic routing that adapts endpoint selection based on real-time contextual analysis of each request. The rules engine dynamically evaluates factors such as request content, user profile, device context, and management rules to determine the appropriate AI endpoint. This dynamic approach allows enterprise resources to be efficiently utilized by authorized users while automatically preventing unauthorized access by routing suspicious or personal requests to appropriate endpoints.
3Device complexity
If a simple routing mechanism is used, then system complexity is reduced, but intelligent routing capability and compliance enforcement are lost
Solution Approach 1:
The patent segments the routing system into distinct functional components: a rules engine that evaluates management rules, a contextual analysis module that assesses request characteristics, and a routing decision module that selects the appropriate endpoint. This segmentation allows the system to maintain low-level simplicity while incorporating advanced intelligent routing capabilities through modular architecture, where each component handles a specific aspect of the routing decision.
Data Source
AI summary
The invention provides a rules engine that manages user requests within an interface integrating multiple AI platforms and AI Models. Upon receiving a query, the engine assigns scores based on factors like management rules, user preferences, and contextual information. Determinative scores, such as those enforcing strict enterprise policies, can override others, leading the engine to block or reroute the query. If no score is determinative, the engine forwards the query and associated prompts to a specialized routing AI Model for contextual analysis. Based on this analysis, the rules engine directs the query to the most appropriate AI Model or defaults to the user-designated AI Model. This system balances user intent with rule enforcement, optimizing query processing across various AI platforms while ensuring compliance with enterprise guidelines.