Database Agent Interface for Natural-Language Query Automation

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Solution Overview

Problem

Traditional database management systems require significant manual intervention and are reactive, failing to predict and prevent issues, necessitating specialized expertise and resource allocation.

Innovation Solution

An autonomous database system utilizing agentic AI with intelligent database agents for self-learning, decision-making, and seamless interaction across structured and unstructured data environments, leveraging NLP and ML to automate management operations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Extent of automation

If traditional database management systems are used with manual intervention, then system control and monitoring are maintained, but operational complexity and resource requirements increase significantly

Engineering Contradiction:

Improveautomation of database management operationsVSAvoidsystem complexity

Core Design Contradiction:

Extent of automationVSDevice complexity

Solution Approach 1:

The database system implements self-service through autonomous agents that automatically perform monitoring, optimization, and maintenance tasks without human intervention. The system self-diagnoses issues, adjusts parameters, and executes corrective actions, eliminating the need for specialized manual database administration while maintaining system control.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

An intermediary layer of intelligent agents is introduced between the database infrastructure and users. These agents translate high-level user requests into optimized database operations and automatically handle complex management tasks, simplifying the interface while maintaining system sophistication through the intermediary layer.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Reliability

If reactive database management is used, then immediate response to issues occurs, but issues are not prevented before they occur and downtime increases

Engineering Contradiction:

Improvesystem reliabilityVSAvoiddowntime

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system performs preliminary actions by continuously analyzing database performance metrics, query patterns, and system health indicators to predict potential issues before they occur. Autonomous agents proactively adjust parameters, optimize queries, and prevent failures before they impact system reliability or cause downtime.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

A continuous feedback loop is implemented where the system monitors its own performance in real-time, compares actual metrics against optimal thresholds, and automatically adjusts operations to maintain peak performance. This closed-loop control ensures high reliability by continuously correcting deviations before they become critical failures.

Inventive Principle:

Principle #23Feedback

3Productivity

If specialized expertise is required for database management, then optimal performance can be achieved, but operational costs and training requirements increase

Engineering Contradiction:

Improvequery execution efficiencyVSAvoidease of database management

Core Design Contradiction:

ProductivityVSEase of operation

Solution Approach 1:

The patent replaces the mechanical system of manual expert intervention with an automated intelligent agent system. These agents embody database expertise through machine learning models and rule-based systems, automatically performing optimization and management tasks that previously required specialized human knowledge, thereby maintaining productivity while dramatically improving ease of operation.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

4Loss of time

If manual resource allocation is used, then flexible control over database resources is maintained, but time consumption and operational overhead increase

Engineering Contradiction:

Improvetime for resource allocationVSAvoidease of resource management

Core Design Contradiction:

Loss of timeVSEase of operation

Solution Approach 1:

The system implements dynamic resource allocation where autonomous agents continuously monitor workload patterns, query complexity, and system capacity to automatically adjust resource distribution in real-time. This dynamic adaptation eliminates manual resource allocation tasks while maintaining flexible control, reducing time consumption and operational overhead through automated decision-making algorithms.

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS12499140B1Database interface framework and database agents

Publication Date: 2025.12.16 CENTURYLINK INTELLECTUAL PROPERTY LLC

AI summary

Novel tools and techniques are provided for implementing a database interface framework, database agents, and operations thereof. In examples, a database interface framework may receive a natural language (“NL”) query from a requesting device, may translate the NL query into a database agent query language (“QL”) query, and may send the database agent QL query to a database agent. For each of at least one database, the database agent may receive and translate the database agent QL query into a QL query, from a database agent QL to a database QL that is used by that database, may send the QL query to that database, may receive query results from that database, and may send the query results to the database interface framework. The database interface framework may receive and translate the query results into an NL response, and may send the NL response to the requesting device.