TL;DR Developer teams building RAG applications face specific integration challenges that traditional AI implementations don’t address. For scaling beyond integration patterns, see scaling RAG API applications. For the retrieval-quality layer that sits after first-pass search, see our guide to RAG reranking techniques. Based on industry data showing 73.34% of RAG implementations happening in large organizations […]

TL;DR Production RAG API implementation requires battle-tested patterns for security, scalability, and reliability. For deeper production scaling guidance, use the production RAG API applications guide. For the retrieval-quality layer that sits after first-pass search, see our guide to RAG reranking techniques. This guide uses real production code from the CustomGPT Starter Kit—a complete implementation currently […]

TL;DR This guide demonstrates how to build production-ready RAG applications using proven implementation patterns from real-world deployments. Instead of theoretical examples, we’ll use actual code from the CustomGPT Starter Kit and working examples from the CustomGPT Cookbook. If you are still deciding which framework layer to use before writing code, compare LangChain, LlamaIndex, Haystack, and […]

TL;DR This hands-on tutorial walks you through getting started with RAG APIs and building your first RAG-powered application from scratch. You’ll learn to set up a RAG API, upload your data sources, create a functional chat interface, and deploy a working application—all in under 30 minutes. After the first build, the next step is scaling […]

TL;DR The choice between RAG API vs traditional LLM APIs comes down to accuracy, currency, and domain expertise. Traditional LLM APIs like OpenAI’s GPT-4 provide broad general knowledge but suffer from knowledge cutoffs, hallucinations, and lack of domain-specific expertise. For regulated finance use cases, see the compliant financial RAG systems. RAG APIs solve these problems […]

If you need the lower-level stack view, the RAG system components guide walks through retrieval, augmentation, and generation. For regulated finance use cases, see the financial services RAG implementation. When you are ready to move past the basics, read RAG API applications in production. When building against a RAG API, review the RAG API chunking […]