Bot Engine Abstraction for Multi-Channel Flexibility
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Solution Overview
Problem
Current chatbots are inflexible, often limited to a single language and communication channel, requiring manual connection to external components using proprietary information, which restricts their adaptability and functionality.
Innovation Solution
A bot engine abstraction system utilizing two abstraction layers to intercept and convert messages from various channels into a generic format, allowing interaction with multiple messaging channels and external components, including analytics and translation services, to create responsive interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a chat bot is designed to support multiple languages and communication channels, then the adaptability and versatility of the chat bot is improved, but the device complexity and implementation difficulty increase
Solution Approach 1:
The patent introduces abstraction layers as intermediary components between the chat bot engine and external components/messaging channels. These abstraction layers provide standardized interfaces that hide the complexity of multiple platforms, allowing the chat bot to interact with various messaging channels and external services through uniform methods without directly implementing platform-specific logic.
Solution Approach 2:
The chat bot engine is designed with universal interfaces and abstraction layers that enable it to work with multiple messaging channels (WhatsApp, Facebook Messenger, etc.) and external components (analytics services, translation services, etc.) through a common set of methods. This multi-functional design allows a single chat bot instance to serve multiple purposes and platforms without requiring separate implementations for each.
2Adaptability or versatility
If multiple platform-specific chat bot instances are created to support different channels, then the chat bot can interact with various messaging channels, but the quantity of components and data storage requirements increase
Solution Approach 1:
The patent implements a universal chat bot engine that can handle multiple messaging channels through standardized interfaces. Instead of creating separate chat bot instances for each platform, the system uses a single engine that interacts with different messaging channels through abstraction layers, reducing the quantity of components needed while maintaining multi-channel support.
Solution Approach 2:
Abstraction layers serve as mediators between the single chat bot engine and multiple messaging channels. These layers translate platform-specific protocols into unified interfaces, allowing one chat bot instance to communicate with various channels without requiring platform-specific instances, thereby reducing the number of components and data storage needs.
3Adaptability or versatility
If manual connection to external components is implemented using proprietary communications information, then the chat bot can access external services, but the ease of operation and maintenance decrease
Solution Approach 1:
The patent introduces abstraction layers as intermediaries between the chat bot engine and external components. These abstraction layers provide standardized interfaces that simplify connections to external services such as analytics services and translation services. Instead of manually configuring proprietary communication protocols for each external service, the abstraction layers handle the complexity, making operations and maintenance easier.
Solution Approach 2:
The abstraction layers are designed to automatically manage connections to external components, reducing the need for manual configuration and maintenance. The system self-manages the integration details, allowing operators to interact with external services through simplified interfaces without dealing with proprietary communication protocols directly.
Data Source
AI summary
A system, method, and computer program product are provided for performing bot engine abstraction. In use, a message is received at a bot engine from a messaging channel, utilizing a first abstraction layer. Additionally, one or more external components are accessed by the bot engine, utilizing a second abstraction layer, to create a response to the message. Further, the response is sent from the bot engine to the messaging channel, utilizing the first abstraction layer.