What is Retrieval Augmented Generation (RAG)?

Some large language models train directly on your data and may not always provide accurate responses. They can also produce less relevant results compared to searches that combine lexical and semantic analysis. Nuqta's RAG-as-a-Service (RAGaaS) addresses these issues by integrating retrieval augmented generation, ensuring more precise and contextually appropriate outputs.

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Top-Tier Retrieval – Enhanced Efficiency

Nuqta utilizes hybrid search approach combining semantic search through large language models and boolean exact matches. This method efficiently identifies the most relevant products, support cases, and documents, ensuring that responses from your Nuqta-powered chatbots, Q&A systems, and conversational apps are based solely on pertinent information, discarding the irrelevant.
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Privacy – Ownership and Control of Data

Nuqta emphasizes privacy by not training models on your data, eliminating risks associated with personal, business, or sensitive information. Our zero-shot large language models are pre-tuned to handle various business queries effectively, making retraining unnecessary. This approach ensures that our models generate accurate summaries and chat responses based on pre-existing data optimization.