AI Agent Orchestration Layer for Database Access Provisioning
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Solution Overview
Problem
Existing systems for managing interactions between cloud computing environments and generative language models are limited, necessitating improved methods to integrate these models into cloud-based infrastructure for enhanced functionality.
Innovation Solution
A computing services environment equipped with an autonomous agent platform that enables the creation and execution of customized autonomous agents, capable of performing operations such as processing natural language input, retrieving data, generating text, and coordinating with other systems, while supporting multi-agent frameworks and multi-planner architectures to facilitate seamless integration and coordination among agents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If autonomous agents are integrated into cloud computing environments to enhance functionality, then system capabilities and automation are improved, but system complexity and management overhead increase
Solution Approach 1:
The patent introduces an intermediary management layer between cloud computing resources and autonomous agents. This layer handles agent lifecycle management, resource allocation, and coordination, thereby reducing the complexity burden on individual components while maintaining high automation capabilities. The intermediary abstracts complex interactions into standardized interfaces.
Solution Approach 2:
The system segments autonomous agents into modular components with defined interfaces and responsibilities. Each agent operates as an independent unit with specific functionalities, allowing for easier management, deployment, and scaling. This segmentation reduces overall system complexity by breaking down monolithic agent structures into manageable units.
2Adaptability or versatility
If multiple autonomous agents are deployed to perform diverse operations, then system versatility and functionality are improved, but coordination difficulty and management overhead increase
Solution Approach 1:
The patent implements a universal agent framework that provides common functionalities and standardized interfaces for all autonomous agents. This universal layer handles communication protocols, resource access, and coordination mechanisms, enabling diverse agents to work together seamlessly. The multi-functional framework reduces coordination complexity by providing a common foundation for all agent interactions.
Solution Approach 2:
The system incorporates feedback mechanisms where agents report their status, resource usage, and task completion to a central coordination layer. This feedback enables dynamic adjustment of agent assignments, resource allocation, and conflict resolution. The feedback loop maintains system versatility while managing coordination complexity through real-time monitoring and adaptation.
3Adaptability or versatility
If generative language models are integrated with cloud systems, then functional capabilities are improved, but integration complexity and computational requirements increase
Solution Approach 1:
The patent introduces an intermediary layer between generative language models and cloud computing systems. This intermediary handles model deployment, inference management, and result integration, thereby simplifying the integration process. It abstracts the complexity of model-serving infrastructure and provides standardized interfaces for consuming generative model outputs within cloud workflows.
Data Source
AI summary
A computing services environment may include application servers providing computing services including access to a database system, a unified metadata framework including autonomous agent definitions referencing action definitions defining a plurality of actions capable of being performed within the computing services environment, an agent service configured to instantiate an autonomous agent instance based on an autonomous agent definition, and an orchestration layer configured to determine an orchestration plan based on novel planning text generated by a generative language model. The orchestration plan may include a subset of the plurality of actions identified in the novel planning text. The computing services environment may execute the subset of the plurality of actions within the computing services environment.