Telephony Bot Configuration via Generative Prompts for Call Routing
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Solution Overview
Problem
Deploying call center bot technology is complex and costly, making it inaccessible to small businesses and sole proprietors, and managing call allocation to human bots with appropriate expertise is challenging.
Innovation Solution
An automated configuration system that uses a generative model to instantiate bots based on user input, allowing end users to configure a bespoke call center service through a telephony interface, scaling bot deployment efficiently and adapting existing bots without manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automated call center bot technology is deployed using skilled engineers for configuration and integration, then the system reliability and functionality are improved, but the deployment complexity and cost increase significantly
Solution Approach 1:
The system enables end users to autonomously configure and deploy automated call center bots through intuitive voice-based interaction. Users can describe their call center needs in natural language, and the system automatically generates and deploys the appropriate bots without requiring manual intervention from skilled engineers, thereby reducing deployment complexity while maintaining system reliability
Solution Approach 2:
The patent replaces complex manual configuration processes with automated AI-driven systems. Instead of requiring engineers to manually configure bot parameters and integrate systems, the invention uses generative AI models to automatically generate configuration parameters and orchestrate bot deployment based on voice-based user requirements, significantly simplifying the deployment process
2Manufacturing precision
If manual configuration and integration of automated call center bots is performed by skilled engineers, then the integration precision is improved, but the time required for deployment increases
Solution Approach 1:
The system performs preliminary configuration actions automatically during the bot generation phase. The AI model pre-configures all necessary bot parameters, integration settings, and system integrations before deployment, so that when users deploy the bots, everything is already prepared and configured correctly, eliminating time-consuming manual configuration while maintaining integration precision
Solution Approach 2:
The patent replaces manual engineering configuration tasks with automated AI systems that generate precise configuration parameters and orchestrate integration automatically. The generative AI models handle the complex tasks of parameter generation and system integration that previously required skilled engineers, reducing both time and maintaining precision
3Ease of operation
If call allocation is manually managed to match human bots with appropriate expertise, then the service quality is improved, but the operational complexity increases
Solution Approach 1:
The system enables automated self-allocation of calls to bots based on their configured expertise and capabilities. Each bot is automatically configured with specific expertise parameters during generation, and the system autonomously routes incoming calls to the most appropriate bot without requiring manual intervention, thereby maintaining high service quality while reducing operational complexity
Solution Approach 2:
The system implements feedback mechanisms where bot performance and call handling results are continuously monitored and fed back into the system. This feedback is used to automatically adjust call allocation strategies and refine bot configurations, enabling the system to improve service quality over time while managing operational complexity through automated adaptive behavior
Data Source
AI summary
A configuration system receives, from an endpoint node of a communications network, information about a desired bot configuration. The endpoint node and the configuration system are in the communications network. The configuration system sends a request comprising a system prompt and the received information to a generative model. The configuration system receives a response to the request, the response comprising a plurality of further system prompts for implementing the desired bot configuration. For each of the plurality of further system prompts, the configuration system triggers instantiation of a bot at a node of the communications network. The instantiated bot comprises the further system prompt. The configuration system sends configuration to a voice interface, to configure the voice interface such that a telephony call associated with the endpoint node has at least one of the instantiated bots as a participant on the telephony call.