LLM Assistant Interface for Executing Data Analytics Tasks
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Solution Overview
Problem
Current data analytics environments lack seamless integration of digital tools for automating repetitive tasks, leading to inefficiencies and fragmented user experiences, as employees resort to manual methods despite available APIs and AI systems that only provide instructions without executing actions.
Innovation Solution
An interactive digital assistant interface utilizing a machine learning model (LLM) to interpret user requests and execute tasks such as processes and APIs, enabling voice or text commands to automate daily office tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If AI systems provide lists of steps or instructions for tasks, then users receive guidance on how to perform tasks, but users must still manually follow instructions and the AI cannot execute actions autonomously
Solution Approach 1:
The AI system performs self-service by autonomously executing tasks through the digital assistant interface. The system receives natural language commands, interprets them, and automatically performs actions such as creating documents, sending emails, or accessing data without requiring users to manually follow step-by-step instructions. This transforms the AI from a passive instruction provider to an active task executor.
2Adaptability or versatility
If multiple digital tools are integrated across various platforms, then comprehensive functionality is achieved, but integration remains less than seamless resulting in fragmented user experience
Solution Approach 1:
The digital assistant interface provides universality by serving as a single point of interaction that consolidates multiple digital tools and platforms. Users can access and control various applications, data sources, and services through one unified interface that understands natural language commands, eliminating the need to navigate between different platforms and improving the seamlessness of the user experience.
3Ease of operation
If employees use traditional manual command and data entry methods, then users maintain control over tasks, but significant time is consumed and attention is diverted from creative activities
Solution Approach 1:
The system replaces manual mechanical operations with automated AI-driven processes. Instead of users manually typing commands, navigating interfaces, and following step-by-step procedures, the AI system uses natural language processing to understand and execute tasks automatically. This substitution of mechanical manual operations with intelligent automation significantly reduces time consumption while maintaining user control through natural language interaction.
Data Source
AI summary
An interactive digital assistant action interface includes a computer including processors that provide access to a data analytics environment, a chat-assistance service or application, and a large language model (LLM). The chat-assistance service or application delivers to the LLM a prompt corresponding to a received query and a desired task is determined based on the LLM receiving the prompt. One or more processes, steps, and/or APIs of the determined desired task are executed at the data analytics environment, and results of the one or more processes, steps, and/or APIs of the determined desired task being executed at the data analytics environment are provided.