Cross-Application Data Mapping With Reusable Templates and Stitches
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Solution Overview
Problem
Current technologies require manual coding for each repetitive task, leading to significant productivity loss and limited automation capabilities, particularly in tasks like copying and pasting information between different applications, which are transient and temporary.
Innovation Solution
A system and method for automating repetitive tasks by creating templates and stitches that link elements between sources and sinks, utilizing machine learning to identify relevant data and share these across users and workflows, thereby reducing the need for manual copying and pasting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual coding is used to develop solutions for each repetitive task, then task automation is achieved, but productivity is severely limited and over 600 productive hours are lost annually per worker
Solution Approach 1:
The patent creates a universal automation system that can handle multiple different repetitive tasks across various applications through a single platform. The system uses templates and stitches that can be reused across different sources and sinks, eliminating the need to code separate solutions for each task. This multi-functionality directly addresses the productivity loss by enabling one system to automate many different copying and pasting tasks that previously required individual coding efforts.
Solution Approach 2:
The system performs preliminary action by pre-defining templates containing source elements and pre-establishing stitches between sources and sinks. These templates and stitches are created in advance and can be automatically applied when needed, eliminating the need for manual task-by-task automation coding. The machine learning component also performs preliminary analysis to identify automation opportunities before manual intervention is required.
2Extent of automation
If coding is required for each repetitive task solution, then task-specific automation is achieved, but the number of people who can automate tasks is limited to competent coders
Solution Approach 1:
The system enables self-service automation by allowing users to define their own templates and stitches without requiring programming knowledge. The machine learning component automatically analyzes user workflows and suggests automation opportunities, enabling non-coders to create automated solutions for their specific tasks. The visual template and stitch creation interface allows users to configure automation rules through simple selections rather than coding.
Solution Approach 2:
The patent introduces an intermediary machine learning system that acts as a mediator between the user and the automation process. This intermediary analyzes user behavior, identifies repetitive tasks, and automatically generates automation templates and stitches. This intermediary layer translates complex automation logic into user-friendly operations, enabling non-coders to benefit from automation without needing to understand the underlying code.
3Ease of operation
If templates and stitches are created for specific users, then user-specific automation is achieved, but sharing and reusability across users is limited
Solution Approach 1:
The patent merges individual user templates and stitches into a shared organizational repository. Users can contribute their customized templates and stitches to this shared space, where they become available to other users. The system combines the benefits of user-specific customization with organizational-wide sharing, allowing templates created for one user's specific needs to be reused and adapted by others performing similar tasks. This merging eliminates the duplication of effort across users while maintaining the ability to customize when needed.
Data Source
AI summary
A method and system for efficiently and automatically moving electronic data from a source, such as a website, to a sink, such as an electronic document; and building, training, and updating the system is provided. Generally, the method uses a system that employs a template for a source that contains labels associated with particular subject matter type of data, and a stitch or electronic link that associate the labeled data to a specific sink.