Data & AI

Nuclia-managed RAG, combined with ChatGPT at Azure’s infrastructure, takes your search and find experience to new heights by generating AI-powered answers from unstructured data. Leverage ChatGPT’s sophisticated language understanding and generation capabilities to reveal valuable insights without manual effort.

The answer provided by a RAG solution like Nuclia will always depend on how precise the question is. The more information you provide, the more accurate the answer will be. Unfortunately, the user might assume that the system has more context than it actually does. For example, imagine your company is running an online avatar creation studio and you provide the following details about the different subscription plans:

One of the most powerful aspects of Nuclia is its ability to find the perfect combination of embeddings, LLMs, prompts, and retrieval strategies tailored to any specific use case. Whether you are dealing with highly specialized industry data or general-purpose information, Nuclia’s flexible framework allows you to configure and optimize every aspect of your RAG process. This means that no matter your specific requirements, you can rely on Nuclia to deliver the most effective and efficient results.

Nuclia’s RAG evaluation tools, REMi and nuclia-eval, can be used to identify and resolve issues in a failing RAG pipeline. The tools are based on the RAG Triad framework, which evaluates the query, contexts, and answer in relation to each other using these metrics: