AI Interactive Agents With Dynamic Module Selection and Permissions
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Solution Overview
Problem
Existing business process automation systems lack adaptability and security, as they involve fixed sequences of steps and do not account for user permissions, and AI systems fail to intelligently determine when to call external functions.
Innovation Solution
A framework and set of tools for constructing AI-guided interactive agents that dynamically determine process paths, allow for user-specific permissions, and enable intelligent decision-making on function calls, incorporating modular modules with defined input/output schemas and user-specific credentials.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If fixed sequences of steps are used in business process automation systems, then the system structure is simple and easy to implement, but the system lacks adaptability and cannot dynamically adjust to different conditions
Solution Approach 1:
The patent implements dynamic business processes where the sequence of steps is not fixed but determined at runtime based on conditions and AI decisions. The system allows processes to adapt and change their execution path dynamically, moving from static predefined sequences to flexible runtime-determined sequences, thereby resolving the contradiction between adaptability and system complexity.
Solution Approach 2:
The patent segments the business process into modular components that can be independently selected and executed. By breaking down the process into discrete, interchangeable steps that can be dynamically assembled based on conditions, the system achieves adaptability without requiring complete redesign of the entire process structure, thus managing complexity while improving versatility.
2Adaptability or versatility
If AI systems provide extension capability with external function definitions, then the system can incorporate data from business systems, but there is no intelligence or adaptability for when to call external functions or how to do it
Solution Approach 1:
The patent enables the AI system to autonomously decide when and how to call external functions without human intervention. The AI agent self-determines the appropriate timing and parameters for function calls based on the current context and business goals, implementing self-service automation that improves both intelligence and automation level simultaneously.
Solution Approach 2:
The system incorporates feedback mechanisms where the AI agent continuously monitors the state of business systems and adjusts its function call decisions based on observed outcomes. This feedback loop enables intelligent adaptation, allowing the system to learn from past interactions and improve its automation decisions over time, resolving the contradiction between adaptability and automation level.
3Reliability
If applications are called in the context of a highly privileged integration account, then the system can access all necessary resources, but security and safety are reduced by not taking into account the calling user's permissions
Solution Approach 1:
The patent applies the principle of local quality by assigning different permission levels to different users and contexts rather than using a single high-privileged account for all operations. Each user's AI agent operates with the specific permissions appropriate to their role, ensuring security while maintaining system functionality. This localized permission approach resolves the contradiction between security and efficiency by eliminating the need for excessive privileges.
Solution Approach 2:
The system introduces an intermediary layer that manages permission verification and credential handling between users and business systems. This intermediary mechanism ensures that AI agents can operate efficiently with appropriate permissions without compromising security, as the permission management is handled automatically through the intermediary rather than requiring manual permission escalation.
4Ease of manufacture
If modular modules with defined input/output schemas are used in interactive agents, then the system achieves better organization and reusability, but the device complexity increases due to module selection and configuration
Solution Approach 1:
The patent implements universal module designs that can serve multiple functions and be reused across different interactive agents. By creating modules with standardized interfaces and multi-functional capabilities, the system reduces the need for custom module configuration and selection, thereby easing construction while managing complexity through reuse rather than proliferation of specialized components.
Data Source
AI summary
A system may initiate generation of an interactive agent to perform one or more tasks, the interactive agent including at least one module of a set of modules, each of the set of modules providing a tool configured to perform a task. The system may determine the at least one module for the interactive agent including selecting the at least one module from among the set of modules. In some cases, the system may initiate a process of the interactive agent to perform the one or more tasks using the at least one module. The various modules may represent functionality that may be interchanged to curate the functionality of the interactive agent. In some implementations, an artificial intelligence model may provide interaction, select modules, configure tools, or perform other guidance.