![case study](https://cdn.quantiphi.com/2024/02/35f9c270-cs-virtual-agent-to-support-distance-learning-01.png)
Virtual Agent to Support Remote Learning
EducationBusiness Impacts
92%
Accuracy during query resolution
1s
Average response time
5K
Unique sessions within first 10 days of launch
24/7
Live chat availability
Customer Key Facts
- Location : Ontario, Canada
- Industry : Education
Problem Context
To support its continuous learning initiatives amid the COVID-19 pandemic, the Upper Grand District School Board launched an online learning program for its 35,000 student base that was isolated at home. However, with many parents and students new to remote learning, Upper Grand administration was inundated with an unprecedented number of inquiries for reliable information pertaining to online safety and technical support.
Challenges
- Intents clashing due to similarity in phrases
- Dialogflow’s integration to CMS to receive real-time responses
- Building accelerators to automate changes from the development environment to the production environment of CMS and Dialogflow agent
![](https://cdn.quantiphi.com/2024/02/0b5bb67a-challenges-virtual-agent-to-support-distance-learning.png)
Technologies Used
![Dialogflow](https://cdn.quantiphi.com/2024/02/6a1ff213-dialogflow-logo.png)
Dialogflow
Google Cloud
![Node.js](https://cdn.quantiphi.com/2024/02/node.js-2.png)
Node.js
Effectively Handling Incoming Queries Surrounding Online Safety And Technical Support For Students And Parents
Solution
To effectively respond to the large influx of queries, Upper Grand partnered with Quantiphi to develop a Rapid Response Virtual Agent capable of providing quality, round-the-clock support. The bot handled 3,000 queries within the first week of implementation, creating a positive experience for students and parents and significantly reducing the workload of administrative staff.
Quantiphi integrated the virtual agent with Upper Grand's existing website as well as a content management system, Google Sheets, for easy update and modification of intent responses. The agent handles 1,000 queries per day and is trained to handle 20 distinct FAQs.
Result
- Cost savings
- Faster query resolution
- Reduced workload for professors, teachers and support staff