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EBElisé Baraka M.ebmurha.hashnode.devApr 14 · 8 min read

Building a RAG Engine — Part 2: An Interface to Evaluate It

Part 1 ended with a pipeline operated fully from the command line. I could ingest documents, run a query, and get an answer wired to evidence. What I didn't have was the UI. I needed an interface to t

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CSCheon Sejuneliosdevlog.hashnode.devApr 11 · 3 min read

Building a High-Precision Travel Guide: Optimizing RAG for a Jeju Island AI Chatbot

Introduction: The Limits of Vanilla LLMs When building a tourism assistant for a specific location like Jeju Island, generic LLMs often fall short. They might hallucinate trail names, provide outdated

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AAdityarag-implementation.hashnode.devApr 9 · 1 min read

What is RAG ?

RAG stands for Retrieval Augmented Generation. RAG helps to improve LLM ( Large Language Model) accuracy by retrieving data from external, trusted data source before generating a response. RAG is an A

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YMYoshi Manyoshi-m.hashnode.devFeb 28 · 6 min read

A few quick lessons from building agentic RAG systems

TL;DR I built an agentic RAG system for a cleaning robot company to help technicians troubleshoot faster using tickets, manuals, and product docs. The biggest thing I learnt: the “agent” part is not

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MMMaithri Medamaithri.hashnode.devFeb 14 · 5 min read

PageIndex RAG: A Smarter Way to Do Retrieval for Long Documents

You built a Retrieval Augmented Generation (RAG) system. It works beautifully on small documents. Answers are grounded, citations look clean, and latency is reasonable. Then someone uploads a 300 page PDF. Suddenly: Answers mix unrelated sections C...

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GWGirma Wakeyoflutter-mistake.hashnode.devJan 30 · 4 min read

Build a Production-Ready AI Document Brain: A No-Nonsense Guide to RAG SaaS

Let’s be real: most companies are drowning in a sea of PDFs. Contracts, handbooks, ancient policy docs—it’s a mess. Usually, employees waste half their day hunting for one specific clause. And if you try to just throw a generic ChatGPT at the problem...

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JMJeet Mukherjeethemukherjee.hashnode.devNov 17, 2025 · 18 min read

How to Build an AI-Powered Legal Research Assistant (with Qdrant at Its Core)

GitHub: https://github.com/Jeet009/legal-assistant-qdrant 1. Introduction: The Legal Profession Meets AI Legal work depends heavily on information: facts, precedents, statutory interpretation, and patterns hidden across thousands of judgments. The mo...

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SRSalman Rasheedproduction-python-api-aws-deployment-lessons.hashnode.devNov 14, 2025 · 4 min read

From Render Roadblocks to AWS Resilience: Lessons from Shipping a Production Python API

Every developer knows the feeling: your application works perfectly on localhost, but deployment is where the real boss battle begins. I recently went through this journey while shipping the backend for my new portfolio project, a journey that starte...

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STShubham Tribediqubridai.hashnode.devOct 26, 2025 · 3 min read

Top 5 Practical Use Cases of Qubrid RAG

Learn about the different use cases of Qubrid RAG - a flexible, multimodal assistant that works with your documents, images, and research papers to deliver instant, contextual, and actionable insights. Financial & Operational Dashboards - Summarize a...

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LSLilly Scottlillyscott.hashnode.devOct 22, 2025 · 39 min read

Boost Performance with Tailored RAG Solutions

So, you've heard about RAG, or Retrieval-Augmented Generation, and how it's supposed to make AI smarter by giving it access to extra info. But sometimes, it's not quite hitting the mark. Basic RAG can be a bit clunky, pulling in the wrong stuff or ju...

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Trending tags this week

Building a RAG Engine — Part 2: An Interface to Evaluate It

Building a High-Precision Travel Guide: Optimizing RAG for a Jeju Island AI Chatbot

What is RAG ?

A few quick lessons from building agentic RAG systems

PageIndex RAG: A Smarter Way to Do Retrieval for Long Documents

Build a Production-Ready AI Document Brain: A No-Nonsense Guide to RAG SaaS

How to Build an AI-Powered Legal Research Assistant (with Qdrant at Its Core)

From Render Roadblocks to AWS Resilience: Lessons from Shipping a Production Python API

Top 5 Practical Use Cases of Qubrid RAG

Boost Performance with Tailored RAG Solutions