One of the greatest weaknesses of AI agents that read and understand vast amounts of enterprise data is "hallucination"—the ...

Jeongho Park, engineer at GraphAI and second author; Donghyoung Han, CTO of GraphAI and third author; Geonho Lee ...

Artificial Intelligence (AI) agents based on Retrieval-Augmented Generation (RAG) technology are rapidly proliferating. RAG ...

One of the greatest weaknesses of AI agents that read and understand vast amounts of enterprise data is "hallucination" — the generation of ...

An intelligent SQL RAG text-to-SQL system that converts natural language questions into optimized SQL queries, executes them against a PostgreSQL database, and returns human-readable insights.

Retrieval-augmented generation (RAG) has become the de facto standard for grounding large language models (LLMs) in private data. The standard architecture — chunking documents, embedding them into a ...

Large Language Models (LLMs) have transformed how we interact with information. However, their reliance solely on internal knowledge can limit the accuracy and depth of their responses, especially ...

Connecting an LLM to your proprietary data via RAG is a massive liability; without document-level access controls, your AI is just one prompt away from exfiltrating your IP. In the enterprise SaaS ...

Retrieval-augmented generation (RAG) has emerged as a pivotal framework in AI, significantly enhancing the accuracy and relevance of responses generated by large language models (LLMs) leveraging ...

RAG is transforming AI apps, and vector databases are the engine behind accurate, real-time responses Choosing the right vector database can make or break performance, scalability, and user experience ...

Data teams building AI agents keep running into the same failure mode. Questions that require joining structured data with unstructured content, sales figures alongside customer reviews or citation ...

Traditional RAG systems struggle bridging structured SQL databases and unstructured document collections (a challenge we call the modality gap), leading to incomplete reasoning and hallucinations.