Multi-Modal Test Automation Orchestration for Real-Time Collaboration

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Solution Overview

Problem

Modern DevOps environments face challenges with non-technical users struggling to understand and utilize automated test components due to complexity, lack of real-time collaboration, context management, and inefficiencies in managing and updating automation scripts, leading to duplication, conflicts, and reduced effectiveness in software testing.

Innovation Solution

A system utilizing supervised learning and Multi-Modal AI for real-time dynamic classification and orchestration of test automation components, enabling non-technical users to input scenarios via handwriting or voice, with AI-driven conflict resolution and context-aware suggestions, ensuring consistency and scalability across distributed environments.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If automated test components are continuously updated and managed in real-time, then software delivery quality and speed are improved, but the complexity of managing and tracking automated components increases

Engineering Contradiction:

Improvesoftware delivery speedVSAvoidcomplexity of managing automated components

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent introduces an intermediary system that acts as a mediator between multiple users and the distributed automated test components. This system provides centralized tracking, real-time notification mechanisms, and coordination capabilities that reduce the management complexity while maintaining high productivity in software delivery.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system implements real-time feedback mechanisms that continuously monitor and track the state of automated test components across distributed environments. This feedback enables automatic updates, conflict detection, and synchronization notifications, allowing teams to manage complex automation suites without manual intervention while maintaining rapid software delivery cycles.

Inventive Principle:

Principle #23Feedback

2Productivity

If non-technical users are enabled to contribute to test scenario creation, then testing effectiveness is improved, but the difficulty of authoring and understanding automated components increases

Engineering Contradiction:

Improvetesting effectivenessVSAvoidease of authoring test scenarios

Core Design Contradiction:

ProductivityVSEase of operation

Solution Approach 1:

The system introduces an intermediary layer that translates between natural language inputs from non-technical users and the technical automated test components. This intermediary handles the complexity of automation framework integration, allowing business users to contribute effectively without needing to understand underlying technical complexities.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Productivity

If multiple users work on automation in a distributed environment, then collaboration and coverage are improved, but conflicts and redundancies in automation code increase

Engineering Contradiction:

Improvecollaboration efficiencyVSAvoidconsistency of automation code

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system implements real-time feedback mechanisms that continuously monitor and track the state of automated test components across distributed environments. This feedback enables automatic updates, conflict detection, and synchronization notifications, allowing multiple users to collaborate effectively while maintaining code consistency and reliability.

Inventive Principle:

Principle #23Feedback

4Ease of operation

If natural input methods like handwriting and voice are supported, then user accessibility is improved, but the complexity of processing and integrating inputs increases

Engineering Contradiction:

Improveuser accessibilityVSAvoidcomplexity of processing inputs

Core Design Contradiction:

Ease of operationVSDevice complexity

Solution Approach 1:

The system introduces an intermediary processing layer that handles the conversion and integration of natural input methods (handwriting, voice) into structured test scenario data. This intermediary manages the complexity of input processing, pattern recognition, and integration with the automation framework, while presenting a simple interface to users.

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS20260050541A1Real Time Dynamic Classification and Orchestration of Test Automated Components Leveraging Supervised Learning and Multi-Modal AI

Publication Date: 2026.02.19 BANK OF AMERICA CORP

AI summary

This invention relates to systems and methods for real-time dynamic classification and orchestration of test automation components in distributed DevOps environments. The system features an Auto Identify Automation (AIA) engine that leverages supervised learning, Multi-Modal Artificial Intelligence (AI), and Generative AI technologies. It includes a Smart Scenario Designer interface that allows users to author test scenarios using handwriting and voice inputs, which are processed in real-time by AI-driven handwriting recognition, voice recognition, and Natural Language Processing (NLP). The system dynamically suggests relevant automated components via a smart bubble pane, facilitating rapid scenario creation. The architecture is tool-agnostic and scalable, with a Shared Workbench Engine that supports real-time collaboration and conflict resolution. The system continuously adapts and improves, ensuring that the automation suite remains consistent, up-to-date, and aligned with evolving software requirements, enabling efficient and user-friendly management of complex test automation processes.