AI Orchestration Engine for Supply Chain Workflow Automation
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Solution Overview
Problem
Existing supply chain management (SCM) enterprise applications developed on codeless platforms face challenges in accommodating diverse operational requirements across industry verticals and regions, with complex workflows and data integration being cumbersome due to the inherent limitations of codeless development frameworks, leading to inefficient process orchestration and customization.
Innovation Solution
A system and method for process orchestration in SCM applications utilizing an AI-based orchestration engine, API, and orchestrator UI to dynamically structure and monitor workflows, coupled with an orchestrator manager, which interacts with configurable components in a codeless platform architecture, enabling dynamic workflow reorganization and execution of SCM operations through data objects mapped to the API.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If codeless platform architecture is used for SCM application development, then development speed and ease of use are improved, but workflow structuring capability and handling of complex data integration deteriorate
Solution Approach 1:
The patent introduces an AI-based orchestration engine as an intermediary component that bridges the codeless platform and complex SCM workflows. This engine automatically structures workflows and integrates data between systems without requiring manual configuration, thereby maintaining ease of development while enhancing workflow structuring capability.
Solution Approach 2:
The system enables self-service through automated workflow generation and configuration. The AI orchestration engine autonomously analyzes requirements, structures appropriate workflows, and configures data integrations without human intervention, allowing the system to serve itself in handling complex orchestrations while the platform remains easy to use.
2Stability of the object's composition
If existing enterprise application architecture is used, then system stability is maintained, but adaptability to diverse operational requirements across industry verticals and regions deteriorates
Solution Approach 1:
The patent implements dynamic adaptability through AI-driven workflow generation that can automatically adjust to different operational requirements. The system dynamically creates and modifies workflows based on specific industry verticals and regional variations while maintaining the underlying stable architecture of the codeless platform.
Solution Approach 2:
The system enables adaptability through parameter changes in workflow configuration and data integration settings. The AI orchestration engine modifies workflow parameters, data mapping configurations, and integration settings to accommodate diverse operational requirements without changing the core system architecture, thus maintaining stability while achieving versatility.
3Adaptability or versatility
If manual workflow structuring is performed in codeless platforms, then customization capability is maintained, but time consumption and operational efficiency deteriorate
Solution Approach 1:
The patent applies preliminary action by having the AI orchestration engine pre-structure workflows and pre-configure data integrations based on analyzed requirements. This preliminary automation eliminates the need for manual workflow structuring while preserving customization capability, as the AI-generated workflows can still be adjusted and configured according to specific needs without time-consuming manual setup.
Data Source
AI summary
The present invention provides a system and a method of Process Orchestration in supply chain management enterprise application developed on codeless Platform architecture. The Process Orchestration includes an API for configuration, AI based Orchestration engine for interaction with one or more configurable components, an Orchestrator UI for monitoring and providing visibility across workflow and an Orchestrator manager for controlling the structure of the workflow.