Case Study: Guesty accelerates RAG chatbot deployment with Qwak

Guesty boosts chatbot engagement 15% with Qwak

Guesty, a property management platform, faced challenges in deploying a scalable RAG-based chatbot. Their difficulties included updating their tech stack for large language models (LLMs), the lack of a vector database, and ensuring the solution could scale from a proof of concept to full production. To address this, Guesty collaborated with Qwak to implement its platform and vector database technology.

Qwak's solution provided a user-friendly platform that enabled Guesty's data science team to build and deploy the chatbot in under a month with minimal engineering support. The implementation used Qwak's Vector DB for storing embeddings and a framework for processing user queries. This resulted in a 15.78% user engagement rate for the chatbot, up from 5.46%, and led to improved operational efficiency, cost savings, and higher guest satisfaction. The Qwak platform also allowed for seamless, one-click scalability from POC to live production.

Guesty