AI Request Routing Rules Engine for Policy-Compliant Model Selection
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Solution Overview
Problem
Current systems lack the capability to dynamically and intelligently route user requests to the appropriate AI endpoint based on the content and context of the request, leading to inefficiencies and potential security breaches when personal and enterprise AI systems are used interchangeably.
Innovation Solution
A rules engine that evaluates requests using management rules, user preferences, and contextual details to determine the most appropriate AI endpoint, with a specialized routing AI Model for nuanced decision-making, ensuring compliance with enterprise policies and user intent.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users can access both personal and managed AI model endpoints freely, then user convenience and accessibility are improved, but resource misallocation and security risks worsen
Solution Approach 1:
The patent introduces an intermediary classification system that automatically analyzes user requests and determines whether they are personal or enterprise-related. This intermediary layer sits between the user and the AI model endpoints, routing requests appropriately without requiring users to manually specify the endpoint type, thus maintaining ease of use while preventing misallocation and security risks
2Adaptability or versatility
If enterprise AI resources are used for personal requests, then user flexibility is improved, but resource consumption and costs worsen
Solution Approach 1:
The patent implements preliminary classification of user requests before they are processed by AI models. By analyzing the request content, context, and user profile in advance, the system pre-determines the appropriate endpoint (personal or enterprise) and routes the request accordingly. This preliminary action prevents unnecessary consumption of enterprise tokens for personal tasks while maintaining user flexibility to access appropriate resources
3Ease of operation
If personal AI models process enterprise requests, then accessibility is improved, but data security and compliance worsen
Solution Approach 1:
The patent introduces an intermediary security layer that classifies requests and determines their appropriate destination. This intermediary analyzes the nature of each request, the sensitivity of the data involved, and the user's authorization level to ensure that enterprise requests are routed to managed AI endpoints that comply with security policies, preventing unauthorized data exposure while maintaining accessible interfaces for users
4Reliability
If intelligent routing is implemented, then resource allocation accuracy is improved, but system complexity worsens
Solution Approach 1:
The patent segments the request processing system into distinct functional modules: a request classification module that analyzes incoming requests, a routing decision module that determines the appropriate endpoint, and an execution module that processes the request. This segmentation allows each component to perform its specific function efficiently, improving routing accuracy while managing system complexity through modular design
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.