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SGSalome Githinjigithinjisal-dev.hashnode.devJul 21 · 4 min read

RAG for Business: How Retrieval-Augmented Generation Can Fix Your Company's Knowledge Problem

Every company has the same quiet problem: knowledge is scattered. It's in Slack threads, PDFs, old emails, wikis nobody updates, and the heads of two or three people who've been there the longest. Whe

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RKRehbar Khanarshhimself.hashnode.devJul 19 · 4 min read

How I Built a RAG Chatbot Into My Portfolio with LangGraph, PGVector & MCP" published: false description: "A deep dive into the Gen-AI assistant on my portfolio — LangGraph agent, RAG over Postgres/pgvector, Redis memory, and live GitHub data via MCP.

Most portfolios have a boring "About Me" paragraph. I replaced mine with something you can talk to — an AI terminal that answers questions about me, pulls my live GitHub activity, and remembers the co

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NANavneet Adarshnavneetadarsh.hashnode.devJul 16 · 5 min read

Why Do We need RAG

Limitations of Using an LLM without External Knowledge Cannot access real time data after training and for that it needs to be train on data and it takes too much costs if you train your LLM two time

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AÖAhmet Özelahmetozel.hashnode.devJul 16 · 40 min read

Building a Local-First OCR + LLM Pipeline for Structured Business Documents

Turning a scanned business document into reliable structured data is not a single-model problem. Optical character recognition is only one stage in a longer system that must handle image quality, page

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SSSuraj S G Dhanvasurajsg23.hashnode.devJul 15 · 13 min read

RAG Was Great. So Why Did I Fine-Tune My Model?

1. How It All Began During our final year of engineering, I built jAIcianVerse, an AI-powered learning platform that I hoped would make studying a little less frustrating. The idea came from something

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PMPrajwal Mglitch-guy0.hashnode.devJul 15 · 6 min read

Understanding RAG: A Simple Guide for Beginners

Introduction: The Problem with LLMs Large Language Models (LLMs) excel at generating text, answering questions, and even writing code. However, they have a critical limitation: they only know what the

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RPRutwik Patilaws-waf-webapp.hashnode.devJul 15 · 4 min read

Beyond Search: Building Knowledge Nexus — The Future of AI-Powered Enterprise Intelligence

How we built an enterprise-grade RAG platform that turns static PDFs into an interactive Knowledge Graph. In the modern enterprise, information isn’t just power — it’s a massive logistical challenge.

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Mmatthewtruong81matthew-codes.hashnode.devJul 8 · 6 min read

RAG or Fine-Tuning? An AI Development Services Comparison

Quick answer: RAG (Retrieval-Augmented Generation) enables the language model to retrieve the most up-to-date information directly from the live knowledge base at query time without retraining. Fine-t

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SDSynfinity Dynamics Pvt Ltdsynfinitydynamics.hashnode.devJul 6 · 7 min read

14 types of RAG (Retrieval-Augmented Generation)

Retrieval-Augmented Generation started as a single, simple idea: retrieve relevant documents, stuff them into a prompt, let the LLM answer. That's it. That's "RAG." But as teams pushed RAG into produc

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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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Trending tags this week

RAG for Business: How Retrieval-Augmented Generation Can Fix Your Company's Knowledge Problem

How I Built a RAG Chatbot Into My Portfolio with LangGraph, PGVector & MCP" published: false description: "A deep dive into the Gen-AI assistant on my portfolio — LangGraph agent, RAG over Postgres/pgvector, Redis memory, and live GitHub data via MCP.

Why Do We need RAG

Building a Local-First OCR + LLM Pipeline for Structured Business Documents

RAG Was Great. So Why Did I Fine-Tune My Model?

Understanding RAG: A Simple Guide for Beginners

Beyond Search: Building Knowledge Nexus — The Future of AI-Powered Enterprise Intelligence

RAG or Fine-Tuning? An AI Development Services Comparison

14 types of RAG (Retrieval-Augmented Generation)

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