rag

Your RAG Finds the Documents. But Which Ones Should Reach the LLM?

Guides filtering retrieved documents before feeding LLM to improve relevance and cost. · for ai product engineers

What's the recommended pattern for implementing row-level security in a LangChain RAG application?

Row-level security pattern · for devtools founders

Trust Before Fusion: QIMG-7 and Source-Aware Resolution for Polluted Multimodal RAG

New multimodal reasoning approach improves performance in polluted environments. · for ai researchers, multimodal model developers

AI builder essentials: tokens, context windows and RAG 101

AI builder essentials · for ai founders, ml engineers

Build a rag legal research assistant that drafts briefs in under 10 minutes

A RAG-based legal assistant can draft briefs in under ten minutes, speeding legal workflows. · for legal tech founders, dev teams

RAG Chunking Strategies That Survive Production: Beyond the 512-Token Default

Improving token limits · for ai engineers

I Built a RAG App on My Laptop Without Paying OpenAI a Single Rupee Here's How

free ai app · for ai founders

Dividing your RAG score by retrieval recall overstates your generation quality, and here is by how much

RAG scores are overstated due to recall bias, prompting more accurate evaluation methods. · for ml researchers, ai engineers

RAG isn't an AI problem. It's a data engineering problem wearing an AI hat.

RAG is data engineering · for ai engineers

I Almost Shipped a RAG Assistant That Lied About APIs That Don't Exist

Highlights hallucination risk when RAG assistants fabricate nonexistent APIs. · for AI product builders

Open Knowledge Format vs RAG: Why Your Agent Should Read a Wiki

AI agents should use Open Knowledge Format for wiki reading rather than plain RAG. · for ai engineers

Architecting for AI-Native Platforms: RAG, LLM Orchestration, and Agentic Patterns

Describes architecture patterns for AI-native platforms using RAG and LLM orchestration. · for platform architects

Designing an End-to-End RAG Architecture from Scratch

Build end-to-end architecture · for ai engineers

How to Make RAG Show Its Evidence: Claim Verification at 15M-Document Scale

Scalable claim verification adds trust to RAG outputs across millions of documents. · for ml engineers

Retrieval is a routing problem. Your RAG stack just hides it.

RAG pipelines should be treated as routing problems to improve retrieval efficiency. · for llm engineers, data scientists

RAG Is Simpler Than You Think

Retrieval-augmented generation can be built with simple components, lowering the barrier for LLM-powered apps. · for llm developers, product engineers

Building a Production RAG Pipeline: Document Processing, Chunking, and Metadata Design

Improves document processing · for ai engineers

A corrective agentic hybrid RAG and an operations-grounded evaluation for a scientific facility

Hybrid RAG improved · for ai researchers, science facility managers

FinSAgent: Corpus-Aligned Multi-Agent RAG Framework for Evidence-Grounded SEC Filing Question Answering

Multi-agent framework for question answering · for nlp devs

9 RAG Techniques That Actually Improve Retrieval Quality

New RAG techniques demonstrably raise retrieval quality for LLM applications. · for AI researchers, LLM engineers