Cross-Platform Generative Interface for Automated Collaboration Tasks
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Solution Overview
Problem
Existing collaborative work environments face challenges in cross-platform tasks due to manual operations and steep learning curves, leading to reduced productivity and inefficiencies in documenting and completing projects across discrete software platforms.
Innovation Solution
A cross-platform generative service that invokes multiple automated assistant services to perform automated content generation and analysis, leveraging a scalable network architecture with large language models and automated assistant services to provide context-aware responses across various software platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If employees manually operate discrete software platforms to complete cross-platform tasks, then task completion is achieved, but productivity decreases and time consumption increases
Solution Approach 1:
The system enables automated self-service across platforms by allowing employees to define once-off and reusable actions that automatically execute across multiple discrete software platforms without manual intervention. The cross-platform service framework automatically invokes platform-specific actions based on a unified action definition, eliminating the need for employees to manually operate each platform individually.
Solution Approach 2:
The patent replaces manual mechanical operations with automated computational processes. Instead of employees manually navigating and operating discrete software platforms, the system uses automated assistant services that invoke platform-specific actions through standardized interfaces, substituting human manual operations with automated service-based mechanisms.
2Reliability
If employees manually document task completion and create work products across platforms, then task documentation is achieved, but resource consumption increases
Solution Approach 1:
The system enables automated self-service across platforms by allowing employees to define once-off and reusable actions that automatically execute across multiple discrete software platforms without manual intervention. The cross-platform service framework automatically invokes platform-specific actions based on a unified action definition, eliminating the need for employees to manually operate each platform individually.
Solution Approach 2:
The system performs preliminary actions by automatically invoking platform-specific actions in response to a unified action definition before employees need to manually document completion. The automated assistant services execute necessary tasks and generate work products in advance, reducing the time employees need to spend on documentation.
3Adaptability or versatility
If discrete software platforms are operated through separate user interfaces, then platform functionality is maintained, but ease of operation decreases due to steep learning curves
Solution Approach 1:
The system implements universality by providing a unified cross-platform service interface that can invoke actions across multiple discrete software platforms. Instead of employees needing to learn separate user interfaces for each platform, the unified interface provides consistent interaction patterns while maintaining access to diverse platform functionalities through standardized action definitions.
Solution Approach 2:
The cross-platform service framework acts as an intermediary between employees and discrete software platforms. It translates unified action definitions into platform-specific operations, mediating the interaction so that employees don't need to directly engage with complex platform-specific interfaces while still achieving the desired functionality.
Data Source
AI summary
Embodiments described herein relate to systems and methods for automatically generating content, generating API requests and/or request bodies, structuring user-generated content, and/or generating structured content in collaboration platforms, such as documentation systems, issue tracking systems, project management platforms, and other platforms. The systems and methods described use a network architecture that includes a generative interface panel having multiple automated assistant services. Each assistant service may access a prompt generation service and a set of one or more purpose-configured large language model instances (LLMs) and/or other trained classifiers or natural language processors used to provide generative responses for content collaboration platforms.


