Abstract
Current artificial intelligence features are often restricted to isolated contexts within specific software applications or entry points. When a user navigates between different tools or surfaces to complete a high-level goal, progress and contextual data are frequently lost, requiring the manual reconstruction of information.
This disclosure describes a method for orchestrating workflows across multiple surfaces using shared contextual data objects. Instead of relying on linear chat histories that may or may not be shared between entry points today, an intelligent data object is created to aggregate relevant information, history, progress states, and dependencies from various interaction points. These objects are both automatically updated by the system and manually referenceable by the user via natural language or interface menus.
The primary purpose of this technology is to maintain continuity and provide holistic task awareness throughout a multi-surface workflow. Efficiency is improved by ensuring that context from one tool directly informs actions in another, thereby reducing cognitive load and streamlining the completion of complex goals.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Lanning, Gabi and Perceval, Peter, "Cross-Surface Workflow Orchestration via Shared Contextual Data Objects", Technical Disclosure Commons, ()
https://www.tdcommons.org/dpubs_series/9929