Bot Framework Tokenization for Cross-Application Integration
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Solution Overview
Problem
Deploying bots across various applications requires significant integration and customization, making it inefficient and labor-intensive.
Innovation Solution
A bot framework with a machine learning implementation that tokenizes requests, matches tokens with stored addresses, and learns from near matches to improve response accuracy and efficiency across multiple applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If bots are deployed across various applications with customized implementations, then response accuracy and application-specific performance are improved, but integration complexity and deployment time increase significantly
Solution Approach 1:
The patent implements a universal bot framework that can serve multiple applications through a common architecture. The framework includes shared components such as a common interface layer, centralized configuration management, and reusable bot templates that can be deployed across different applications without requiring separate customized implementations for each application.
Solution Approach 2:
The bot system is divided into modular segments including independent bot units, separate configuration files, and discrete interface layers. Each bot can be developed, tested, and deployed independently while maintaining compatibility with the overall framework, reducing integration complexity and enabling parallel development.
2Adaptability or versatility
If significant integration and customization are performed for each bot deployment, then bot functionality and application fit are improved, but labor intensity and deployment time increase
Solution Approach 1:
The framework provides pre-configured bot templates, standardized interface definitions, and default configuration settings that are prepared in advance. These preliminary configurations can be directly applied to new deployments, eliminating the need for extensive customization work and significantly reducing deployment time while maintaining application-specific adaptability.
Solution Approach 2:
The system enables deployment of bots across different applications by changing configuration parameters rather than modifying the core bot logic. Applications can be adapted by adjusting parameters such as interface endpoints, configuration files, and runtime settings, allowing rapid deployment without labor-intensive customization.
3Ease of operation
If a bot framework enables seamless integration across diverse applications, then ease of deployment is improved, but system complexity and learning curve increase
Solution Approach 1:
The patent introduces an intermediary framework layer that sits between the bot core and various applications. This intermediary handles application-specific protocols, data formats, and interface requirements, allowing bots to be deployed seamlessly across diverse applications without exposing the underlying system complexity to users. The intermediary translates and adapts communications automatically.
Data Source
AI summary
Methods and apparatus, including computer program products, are provided for a bot framework. In some implementations, there may be provided a method which may include receiving a request comprising a text string, the request corresponding to a request for handling by a bot; generating, from the request, at least one token; determining whether the at least one token matches at least one stored token mapped to an address; selecting the address in response to the match between the at least one token and the at least one stored token; and presenting, at a client interface associated with the bot, data obtained at the selected address in order to form a response to the request. Related systems, methods, and articles of manufacture are also disclosed.