Key highlights

~ 50

faster student query response

30

quicker registration process

30

boost in student engagement

Challenges

  • Manual data preparation for RASA chatbots required significant labor and time.

  • Traditional support methods failed to address student queries about administration and courses.

  • Students struggled to navigate complex administrative processes and course details.

Solution

1.

The solution used a conversational interface that employed natural language processing (NLP) to understand student queries and provide relevant answers.

2

The gen AI model retrieved accurate information from the internal knowledge base on courses, registration, finance, and certification to generate responses.

3.

We continuously refined this model and updated the knowledge base to reflect new information and policy changes.

Impact

Enhanced student support

Provided 24/7 accurate responses and reduced wait times.

Increased administrative efficiency

Reduced workload for administration and tutoring teams.

Tracked application usage

Monitored real-time application usage and engagement.

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