Agentic data science with the Data Agent Kit
cloud.google.com·6h ago
AI Research
arXiv CS.AI·Sep 3·5 min read
Beyond-RAG: Question Identification and Answer Generation in Real-Time Conversations
TL;DR
A new decision support system enhances customer service by identifying questions in real-time and providing answers quickly, reducing average handling times significantly. Deployed at Minerva CQ, it improves efficiency and lowers operational costs.
✦ Why It Matters
Implement a real-time question identification system to enhance customer service efficiency today.
Key Takeaways
- Adopt real-time question identification to reduce AHT.
- Utilize automated workflows to create FAQs from historical data.
- Integrate RAG for generating answers when FAQs are unavailable.
- Deploy systems that provide responses within 2 seconds.
How It Works
The system first identifies customer questions in real time. If the question matches an existing FAQ, it retrieves the answer directly from the FAQ database.
If not, it generates an answer using RAG, which combines retrieval and generation techniques to provide relevant responses quickly.