One of the world's leading AI platforms with enterprise-level LLM and RAG products, increasing productivity and improving customer and employee experience for their clients. Invisible refined training data and provided ideal responses, enabling them to enhance model performance and accuracy efficiently.
The client was facing challenges in evaluating and improving model responses, as existing data lacked thorough annotation and comparison.
Invisible's team stepped in to review partially completed conversations between different models. We analyzed the search results, reference material, and model responses.
Our experts evaluated sufficiency, usefulness, and quality of the responses, ranked them, and created an ideal response by editing the preferred one. Where conversations were incomplete, we extended them and repeated the process.
The client received refined, high-quality annotated data with ideal responses, enabling them to enhance model performance and accuracy efficiently.
