Have you conversed with a virtual agent but were unable to get the information you really required? We all have. This often leads to a sub-par customer experience and the need for human intervention. Bridging the gap where the virtual agent learns to cover a wide range of topics pertinent to its end-users is where the need for a feedback mechanism arises.
Conversational AI today is dependent to a great extent on human knowledge. Virtual agents are developed on a model that depends either on rules or intent classification, and the majority of the intelligence comes from training data that is input by a human on the bot-building platform.
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The need for self-learning AI is increasingly prevalent in this context to consistently improve the performance of the bot. Quantiphi’s sQrutinizer is here to solve this problem for you.
The sQrutinizer is a tool that:
sQrutinizer analyzes those user utterances or phrases that were not recognized by the Google Cloud CCAI as well as those that had a lower confidence score. Using these fallback user utterances and false positives, sQrutinizer helps developers and conversation designers with these two tasks:
With sQrutinizer, designers can focus on the most important aspects of designing great conversations, and leave the intent training to sQrutinizer.
The setup is a simple three-step process –
You can also choose between multiple clustering and classification models so as to achieve the maximum accuracy possible.
sQrutinizer helps ensure that the virtual agent itself will learn to take into account such queries that it was unable to answer earlier, thereby expanding the virtual agent knowledge base via retraining the NLU.
The three primary benefits of the feedback loop are:
To conclude, sQrutinizer helps conversation designers and developers monitor the fallback and false-positive utterances of their virtual agents. Using the results from sQrutinizer, developers can either update the existing intent training to improve the virtual agent performance and efficiency or create new intents to broaden the knowledge base of the bot.
Get in touch with our experts today to explore sQrutinizer and drastically improve your bot performance and, in turn, your customers’ experience.
Contributed by: Kanishk Mehta and Krish Kalro