World’s largest cloud provider and e-commerce company

Fine-tuned a large-scale RAG system using LLM’s for an interactive and safe conversational experience, helping customers find answers to product questions across categories.

About the Client

The world’s largest e-commerce company sought to leverage large language models (LLMs) to help customers find answers to product questions, compare products, receive relevant product suggestions, and otherwise improve the online shopping experience. To achieve the desired interactive, conversational experience, the client needed to fine-tune a large-scale retrieval-augmented generation (RAG) chatbot.


To achieve the organization’s goals, the client’s chatbot development team needed to improve the safety of the LLM’s responses prior to making it available for general consumer use.


Using Centific’s SafeAI framework, our teams annotated data-run workstreams of reinforcement learning from human feedback (RLHF) processes, supervised fine-tuning and red teaming, and created (or transcreated) a variety of content—including model instructions, golden sets, and prompt and response pairs—across a variety of modalities (e.g., text, image, audio, and video).


The client achieved high levels of both safety and performance without having to compromise on one for the other. This made for a more fulfilling and enjoyable online shopping experience.