Catalyst Application for Cross-App Task Extraction and Execution
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Solution Overview
Problem
Existing digital content systems are inflexible and inefficient due to rigid task management functions that require frequent navigation between different computer applications, leading to excessive client device interactions and computational inefficiencies.
Innovation Solution
A catalyst application that integrates with other computer applications to automatically extract tasks from digital content, generating task lists in real-time using a large language model and executing tasks without additional user interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing systems use rigid task management functions fixed to specific applications, then task management is structured and organized, but flexibility and adaptability across different applications are reduced
Solution Approach 1:
The task management system is designed to operate across multiple different applications (email, messaging, video calls, web browsers) rather than being confined to a single application. The system can extract tasks from any application's digital content and execute them, making the task management functionality universal and adaptable to various contexts.
Solution Approach 2:
The system introduces an intermediary task extraction and execution layer that sits between the user and multiple applications. This intermediary component analyzes digital content from different applications, extracts tasks, and coordinates execution without requiring the user to navigate between applications manually.
2Productivity
If existing systems require frequent navigation between multiple applications for task extraction and execution, then comprehensive task management is achieved, but user interaction efficiency and time consumption are reduced
Solution Approach 1:
The system proactively monitors and analyzes digital content across applications in real-time, extracting tasks before the user needs to manually switch applications. By performing task extraction preliminarily and automatically, the system eliminates the need for users to navigate between applications to find and manage tasks.
Solution Approach 2:
The task management system operates continuously in the background, constantly analyzing digital content from multiple applications and maintaining an up-to-date task list. This continuous operation ensures that tasks are extracted and managed without interruption, eliminating the need for users to repeatedly switch between applications to update task information.
3Adaptability or versatility
If existing systems simultaneously run multiple applications for task management and data access, then comprehensive functionality is available, but computational resources and memory consumption increase
Solution Approach 1:
The system extracts only the necessary task-related information from digital content in multiple applications, rather than loading or processing entire application datasets. By extracting specific task elements (actions, deadlines, assignments) from emails, messages, and other content, the system maintains functional comprehensiveness while minimizing computational resource usage.
Solution Approach 2:
The system segments the task management functionality into discrete components: digital content monitoring, task extraction, task storage, and task execution. Each component operates independently and efficiently, processing only relevant data from specific applications rather than loading entire application environments, thus reducing overall computational overhead.
Data Source
AI summary
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for utilizing a catalyst application to analyze digital content of another computer application to generate or extract tasks. The catalyst application can accompany and operate in conjunction with another computer application to extract data from the application and generate tasks. For example, the disclosed systems can scan displayed (or otherwise presented) digital content in an application and can generate a prompt for causing a large language model to identify or extract tasks from the digital content. Through the catalyst application, the disclosed systems can thus implement a large language model to generate a task list from the digital content of another computer application. The disclosed systems can further utilize the catalyst application to automatically execute or perform extracted tasks.