Contact Center Response Generation via Governed API Calls
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Solution Overview
Problem
Natural language processing engines in contact centers often lack integration with data stored by the entity, limiting their ability to access or modify customer information, transaction history, or product information.
Innovation Solution
Integrating a software agent with API calling technology to access data using a governance engine, which generates a data structure readable by the software agent, enabling it to provide informed responses through natural language processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If a natural language processing engine is used in a contact center, then the ability to generate automated responses is improved, but the ability to access and modify stored data (customer information, transaction history, product information) deteriorates due to lack of integration
Solution Approach 1:
The patent introduces an API gateway as an intermediary component that bridges the natural language processing engine and the data storage systems. The gateway receives data access requests from the NLP engine, translates them into appropriate API calls, and returns the requested data. This mediator enables the NLP engine to access customer information, transaction history, and product information without being directly integrated with these systems, thus resolving the contradiction between automation and data access versatility.
2Adaptability or versatility
If API calling technology is integrated with the software agent, then the data access capability is improved, but the system complexity increases due to additional integration components
Solution Approach 1:
The API gateway is designed as a universal interface that handles multiple types of data access requests (customer information, transaction history, product information) through a standardized set of API calls. This multi-functional design allows the gateway to serve various data access needs without requiring separate integration components for each data type, thereby improving data access capability while limiting the increase in system complexity.
3Measurement precision
If the software agent processes multiple requests sequentially, then the accuracy of data-driven responses is improved, but the response time increases
Solution Approach 1:
The system performs preliminary actions by pre-fetching and caching data that is likely to be needed for upcoming requests. When the NLP engine generates a response, the API gateway anticipates subsequent data access needs and retrieves that data in advance, storing it in a cache. This preliminary action allows the system to maintain high response accuracy by having accurate data ready while reducing response time by avoiding redundant data retrieval operations.
Data Source
AI summary
A server may access, during an engagement with a contact center by a software agent, a prompt from a user device. The server may determine, using a natural language processing engine of the software agent, to use an application programming interface call based on the prompt. The server may transmit a request representing the application programming interface call to a governance engine. The server may receive a data structure responsive to the request from the governance engine. The server may generate, using the natural language processing engine, a response based on the data structure.