Customer support

Coursera · boost.ai

Vendor-reportedEducationIn productionEnterpriseLLMLive 2023

Vendor-reported. The customer is named and the numbers are quoted from the source page, but the account comes from the vendor. No independent confirmation.

Reported by boost.ai (vendor self-report). Checked against the source page on 2026-09-06. 4 of 4 figures below appear on that page word for word.

The problem

Coursera needed to scale support, personalize interactions for diverse learner types, and gain strategic insights from conversations without growing its team.

What was deployed

Vendor
boost.ai
Products
boost.ai platform, Generative Action, Boost Agent Orchestrator
Technique
LLM
Build or buy
Bought off the shelf
Deployment
SaaS
Data used
account data, conversation trends, learner-type filtering
Scale
global

What changed

Each row is quoted from the source. Figures we could not find on the page in those words are marked — they are kept, not deleted, so you can judge them.

53%deflection rate

Cora maintains a 53% deflection rate

Quoted word for word from the source

5distinct learner types identified

5 distinct learner types identified and routed by the AI Agent

Quoted word for word from the source

90%+knowledge base coverage

covers more than 90% of all help center topics

Quoted word for word from the source

~30%Chatbot Escalation Impact

Chatbot Escalation Impact: the percentage of human agent support volume that originated as a conversation with the AI Agent. It’s treated internally as a health indicator and is currently sitting at ~30%.

Quoted word for word from the source

support agent time

I can see that it is saving our support agents time

Quoted word for word from the source

In order to further improve our performance and health metrics, we worked with boost.ai to develop more advanced user-type filtering
Bee Strother, Senior Help Content Strategist, Coursera

Difficulties and limits

Sources

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