Digital Avatar Integration for Self-Service Multi-System Data Exchange
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Solution Overview
Problem
Existing electronic information exchange platforms face challenges in scaling up securely, efficiently, and cost-effectively to handle diverse and dynamic data exchange requirements across disparate systems, necessitating complex manual coding and configuration.
Innovation Solution
An intelligent integration system with digital avatars that operate in a distributed computing environment, utilizing avatars to transform data, manage workflows, and apply choreography keys, along with handlers and enrichment rules, to facilitate seamless data exchange across diverse systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual coding and configuration is used for each enterprise system to connect to the electronic information exchange platform, then the system can meet specific data exchange requirements, but the complexity and cost of integration increases significantly
Solution Approach 1:
The system enables self-service through automated discovery and configuration. Enterprise systems automatically publish their data exchange requirements and capabilities, allowing the platform to autonomously match and integrate systems without manual coding. The intelligent agent discovers available services and configurations automatically, eliminating the need for manual integration work for each new system connection.
Solution Approach 2:
The intelligent agent acts as an intermediary between enterprise systems and the electronic information exchange platform. It automatically discovers, matches, and configures integration parameters between disparate systems, serving as a mediator that translates between different system interfaces and the platform's data exchange requirements without manual intervention.
2Productivity
If the electronic information exchange platform scales up to handle more diverse systems and data requirements, then the capability to serve more entities improves, but the cost and time for manual configuration increases
Solution Approach 1:
The system performs preliminary action by automatically publishing and registering data exchange requirements, services, and configurations in advance. Enterprise systems proactively declare their integration capabilities and data models before actual data exchange begins, allowing the intelligent agent to pre-configure integration pathways and eliminate time-consuming manual setup when new systems are added.
Solution Approach 2:
The platform enables self-service scaling by automatically discovering new enterprise systems and their requirements, then autonomously configuring integration parameters without human intervention. This allows the platform to scale productivity by handling more data exchange volume while the intelligent agent manages the configuration workload automatically.
3Manufacturing precision
If custom integration is implemented for each enterprise system with unique requirements, then data exchange accuracy improves, but the integration complexity and cost becomes prohibitive
Solution Approach 1:
The system achieves accurate data exchange through parameter changes by dynamically adjusting integration configuration parameters based on the specific requirements of each enterprise system. The intelligent agent automatically modifies data models, mapping rules, and exchange parameters to match each system's unique characteristics while maintaining data exchange accuracy without requiring custom integration code for each system.
Data Source
AI summary
An intelligent integration system runs a workflow implementation in a test mode with an avatar, a set of handlers, and a choreography. The system receives a message from the second entity to the first entity via their respective avatars. The arrival of data in the message triggers the first entity to invoke an integration activity which utilizes the set of handlers. The integration activity follows the choreography and moving the data through the choreography is defined and governed by a choreography key. The system may stop moving the data through the choreography, determine/generate a handler that can meet a requirement of the choreography key that is not met by the set of handlers, and update the workflow implementation to include the handler. The system may then continue or restart the workflow implementation with the handler that can meet the requirement of the choreography key.