Identify the action or the intent from user’s input and provide more accurate response.

Overview

Extract meaningful information from customer queries, enabling more precise and personalized responses and provide a more engaging and relevant experience.

Personalization

Empower digital agent with personalized responses & recommendations.

Adaption

Adapt to new contexts & user needs rapidly, maintaining relevance in responses.

Automation

Enable automaton of tasks that previously required human interventions.

Experience

Enhance customer satisfaction by with natural & user-friendly conversations.

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Scenario:

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The current chatbot struggles with IT inquiries, lacking precision in tasks like password resets and computer issues. An improved system is needed for more accurate and helpful user assistance.

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Approach:

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  • Improve the digital agent’s understanding of common IT issues through enhanced Natural Language Understanding.
  • Train the NLU model with diverse IT-related sample utterances for better accuracy in intent detection.
  • Monitor the NLU performance based on user’s interactions to improve the accuracy.
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Scenario:

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The current chatbot struggles with IT and HR distinctions, necessitating an improved system for accurate and appropriate user assistance in both departments.

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Approach:

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  • Enhance digital agent’s NLU to discern IT and HR inquiries effectively.
  • Train NLU model with specific IT and HR sample utterances for improved accuracy.
  • Train NLU model with specific IT and HR sample utterances for improved accuracy.
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Scenario:

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The current chatbot struggles to understand nuanced discussions about company policies and employee skill programs, requiring enhancement for more effective responses.

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Approach:

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  • Update the utterances to identify the nuances in the conversations.
  • Train the NLU model with simulations to understand the responses for such complex conversations.