What problem does RAG solve?

It lets a model answer from your specific, up-to-date data instead of only its training, which reduces hallucination and stale answers.

Why are my RAG answers still wrong?

Usually retrieval, not the model — poor chunking or ranking feeds the wrong context. Fix retrieval and reranking first.

Does the prompt matter in RAG?

Yes — how you instruct the model to use (and not exceed) the retrieved context is decisive. Oort has grounding-focused prompts to start from.

Retrieval-Augmented Generation

RAG news — vector databases, retrieval techniques, and grounding LLMs in your own data without hallucinating.

What to know

Retrieval-Augmented Generation grounds an LLM in your own data by retrieving relevant context at query time — the standard way to cut hallucination and answer from private knowledge. The moving parts are chunking, embeddings, retrieval, and reranking. This hub tracks techniques and tooling.

Latest Retrieval-Augmented Generation news

A Coding Guide to Implement a pgvector-Powered Semantic, Hybrid, Sparse, and Quantized Vector Search System

In this tutorial, we build a complete pgvector playground inside Google Colab and explore how PostgreSQL can work as a powerful vector database for modern AI applications. We start by installing PostgreSQL, compiling…

MarkTechPost1d ago

Scaling domain expertise in complex, regulated domains

Discover how Blue J is transforming tax research with AI-powered tools built on GPT-4.1. By combining domain expertise with Retrieval-Augmented Generation, Blue J delivers fast, accurate, and fully-cited tax…

OpenAI9mo ago

Retrieval-Augmented Generation — FAQ

What problem does RAG solve?: It lets a model answer from your specific, up-to-date data instead of only its training, which reduces hallucination and stale answers.
Why are my RAG answers still wrong?: Usually retrieval, not the model — poor chunking or ranking feeds the wrong context. Fix retrieval and reranking first.
Does the prompt matter in RAG?: Yes — how you instruct the model to use (and not exceed) the retrieved context is decisive. Oort has grounding-focused prompts to start from.