Case Study: a leading enterprise AI company improves RAG model accuracy with Invisible Technologies

Ranking and optimizing RAG AI models for leading enterprise AI platform

Invisible Technologies partnered with a leading enterprise AI company to address a challenge with its RAG (Retrieval-Augmented Generation) AI model. The client, a major platform offering enterprise-level LLM and RAG products, was struggling with unrefined training data. Their existing datasets lacked thorough annotation and comparisons, which made it difficult for them to accurately evaluate and improve their AI model's responses.

The solution involved Invisible Technologies' experts performing over 1,100 rating and ranking tasks on the annotated data. They reviewed model conversations, analyzed search results and reference materials, and then ranked the responses. Crucially, they edited the best responses to create ideal answers, significantly refining the training dataset. This process provided the client with high-quality data, enabling them to efficiently enhance their model's performance and accuracy.