The Contextual Model, also known as the LLM Model, analyzes entire case conversations to provide insights and relevant messages for defined quality parameters. The scoring logic is configured to assign scores based on the model output.

Compared to the Classification Model, the Contextual Model offers greater accuracy by analyzing the entire context of the case rather than focusing solely on message or phrase-level analysis.

By comprehensively analyzing entire case conversations, the LLM Model enhances user experience by delivering more accurate and contextually relevant insights.

Supported Languages

The model supports English, Spanish, and German languages for both digital and voice cases.

Example of Contextual Model Scoring on Sprinklr Platform

In the image provided, the Quality Management (QM) model has identified one of the agent messages in the conversation as depicting Courtesy. The model provides an insight statement explaining the reason the agent needs to be courteous, and the relevant messages are highlighted accordingly. As Courtesy is considered a positive parameter, the quality score assigned for this specific parameter is 100.