GeeTest Business Rules Engine Overview
Overview
GeeTest Decision Engine is a unified decision management platform that integrates rule engines, machine learning, algorithm optimization, stream processing, and big data computation. It provides an end-to-end low-code and no-code solution that covers the entire decision lifecycle, including data ingestion, model building, and real-time deployment of decision services.
The platform automates enterprise decision-making processes and enables organizations to operate effectively in complex and dynamic environments. By leveraging predefined rules, strategies, data, and models, it improves both efficiency and decision accuracy. Typical applications include financial services, supply chain optimization, customer relationship management, and medical diagnostics.
Core Capabilities
- Scenario Management: Supports the creation, querying, and management of scenarios. Ensures secure isolation of different customer use cases through multi-tenant design.
- Rule Management: After editing, rules can be updated instantly through real-time hot deployment. A specific rule can be applied independently, while others can run in shadow mode for testing. The outputs of shadow rules are logged to support champion–challenger evaluation.
- List Management: Within orchestrated workflows, custom lists can be queried, added, and deleted, providing greater flexibility for business decision-making.
- Custom Functions: Provides a wide range of customizable function nodes for input parameter calculations within processes, enabling complex orchestration, scheduling, and core function design.
- Real-Time Computation: Provides high-performance synchronous real-time calculations that can be orchestrated and executed at any point within a workflow.
- Real-Time Alerts and Notifications: Triggers downstream notifications when specific conditions are met within a workflow, such as sending email or other types of alerts.
- Visual Editing: Allows rule editing through a drag-and-drop interface.
Advantages of Business Decision Engine
1. Emphasis on Flexibility and Real-Time Capabilities for Complex Scenarios
- Designed with flexibility and real-time responsiveness, surpassing traditional models and static profiling approaches.
- Utilizes sliding window techniques for continuous real-time computation, enhancing the accuracy and completeness of decisions with business data.
- Provides real-time monitoring that automatically triggers alerts on anomalies, enabling rapid response and risk mitigation.
2. Focused on Business Experts, Simplifying the Decision Process
- Allows business experts to work directly with data, using analysis and prediction tools to build decision logic and adjust thresholds without relying on complex coding.
- Makes it easy to capture and reuse expert knowledge, helping teams make decisions faster and more effectively.
3. Low-Barrier Operation, Enabling Cross-Department Collaboration
- Designed with a process-first approach that supports drag-and-drop operations, making it easy to handle complex business logic.
- Provides a visual workflow editor with modular strategy blocks, enabling quick adoption and continuous iteration.
- Separates business rules from system code, allowing full lifecycle management of rule creation, editing, testing, activation, and deactivation, accessible even to non-technical users.
- Uses flowcharts to clearly illustrate decision logic, improving rule transparency, enhancing communication, and facilitating cross-department collaboration.
4. Robust Functionality Ensuring Efficient and Stable System Operation
- Integrates expression evaluation and custom nodes, enabling complex business logic to be processed efficiently through ZEN language and decision table nodes, thereby enhancing rule evaluation efficiency and system stability.
- Reduces semantic deviations in coding, ensuring consistency and maintainability of business rules, which in turn improves overall operational efficiency.
- Allows dynamic modification of business rules, enabling rapid response to changing requirements.