Conversational Interface for Database Customization
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Solution Overview
Problem
In multi-tenant cloud-based database systems, customizing components can be difficult and time-consuming for users without programming knowledge, as they need to navigate complex interfaces and technical aspects.
Innovation Solution
A conversational user interface that allows users to input commands in natural language, which are parsed to identify the desired database action and required attributes, prompting the user for missing information and automatically performing the action without requiring detailed technical knowledge.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a multi-tenant database system allows customization of components, then the system becomes more adaptable to different tenant needs, but the complexity of the customization process increases
Solution Approach 1:
The patent introduces a conversational interface as an intermediary between the user and the complex database customization system. This intermediary translates natural language user intentions into precise database operations, shielding users from the underlying complexity while maintaining full customization capability. The conversational interface acts as a mediator that handles the complexity of parsing user intent, mapping it to database schemas, and executing the customization without exposing users to technical details.
2Adaptability or versatility
If the system provides detailed customization options, then the adaptability increases, but the ease of operation decreases for inexperienced users
Solution Approach 1:
The patent replaces the traditional mechanical interaction model (clicking through complex UI menus, navigating technical interfaces) with a linguistic interaction model. Users communicate their customization needs through natural language conversation rather than manipulating complex interface elements. This substitution eliminates the need for users to understand or navigate complex technical interfaces while preserving full access to customization options through conversational commands.
Solution Approach 2:
The conversational interface enables users to independently perform customization tasks without requiring assistance from system administrators or technical expertise. The system autonomously interprets user conversations, determines the appropriate database operations, and executes the customization actions. This self-service capability allows inexperienced users to access and utilize detailed customization options at their own pace through simple conversation.
3Manufacturing precision
If the system requires users to navigate complex interfaces for customization, then the precision of customization control is maintained, but the time required for customization increases
Solution Approach 1:
The conversational interface performs preliminary actions by proactively gathering and clarifying user requirements through conversation before executing the actual customization. The system anticipates what information is needed, asks clarifying questions in advance, and prepares the customization parameters during the interaction phase. This preliminary engagement ensures precise control over the customization outcome while reducing the time needed for actual implementation, as the system is already prepared to execute the customization immediately after user confirmation.
Solution Approach 2:
The system implements continuous feedback loops during the conversational customization process. As users express their customization needs, the system provides real-time feedback by confirming its understanding, asking clarifying questions, and presenting proposed actions for approval. This feedback mechanism ensures precise customization control by verifying that the system's interpretation matches user intent, while simultaneously reducing customization time by resolving ambiguities during the conversation rather than requiring multiple revision cycles after implementation.
Data Source
AI summary
Computing systems, database systems, and related conversational interaction methods are provided for customizing database components. One exemplary method involves receiving a conversational user input, analyzing the conversational user input to identify a requested action with respect to a database component, identifying a plurality of attributes associated with the requested action with respect to the database component, determining a missing subset of the plurality of attributes based at least in part on the user input, prompting a user for values of the missing subset of attributes, receiving a second conversational user input responsive to the prompt, and performing the requested action with respect to the database component in a database using the second user input.