Problem solved

Need a chatbot that knows your business data inside and out?

Create AI Chat Experiences with Your Own Data: The Complete RAG Pipeline Guide

Create an AI assistant that answers questions using only your content - with zero hallucinations

Step by step tutorial: how to build a production-ready RAG pipeline.

Tutorial: Build a RAG pipeline with LangChain, OpenAI and Pinecone background

Tutorial: Build a RAG pipeline with LangChain, OpenAI and Pinecone

Step by step tutorial: how to build a production-ready RAG pipeline.

Zachary Proser

Build a production-ready AI solution that answers questions from your own content with accurate citations. Includes a complete Jupyter notebook, Next.js example site, and step-by-step instructions.

Step by step tutorial: how to build a production-ready RAG pipeline.

  • Complete End-to-End Solution

    From data processing to deployment, learn every step needed to build a production-ready RAG pipeline

  • Ready-to-Use Jupyter Notebook

    Process your own data with our pre-built notebook that handles chunking, embedding, and vector database creation

  • Next.js Example Application

    Full source code for a modern web application with streaming responses and citation support

  • No Hallucinations, Real Answers

    Learn how to ground AI responses in your actual content for accurate, trustworthy results

Get a free chapter straight to your inbox

What's Included

Everything you need to build production-ready solutions

Jupyter Notebook interface showing data processing and vector database creation

Interactive Jupyter Notebook

A complete, ready-to-run notebook that walks you through data processing, embedding creation, and vector database setup. Simply add your API keys and run each cell to process your own content. Includes detailed explanations of chunking strategies, embedding techniques, and Pinecone integration.

Next.js chat application with streaming responses and citations

Production-Ready Next.js Application

Full source code for a modern web application built with the Vercel AI SDK. Features streaming responses, citation support, related content suggestions, and a beautiful chat interface. Deploy it to Vercel with one click or run it locally for development.

RAG pipeline architecture diagram showing the complete system flow

Comprehensive Step-by-Step Tutorial

Detailed written guide that explains every concept, from RAG fundamentals to advanced implementation patterns. Learn not just how to build it, but why each piece works and how to customize it for your specific use case. Perfect for developers who want to truly understand the technology.

Table of contents

Get a complete overview of everything you'll learn.

"Tutorial: Build a RAG pipeline with LangChain, OpenAI and Pinecone" is a comprehensive guide with practical insights and hands-on examples.

  1. Getting Started

  2. Phase 1: Data Processing

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Expert-crafted solution for real-world applications

This comprehensive package provides everything you need to build production-ready AI systems that understand and answer questions based on your proprietary data.

Tutorial: Build a RAG pipeline with LangChain, OpenAI and Pinecone visualization

What developers say about my work

Learn from someone with 13 years of real-world experience building professional software

When I ran your software, I felt joy
Jim Brikman
Jim Brikman
Co-founder of Gruntwork, OpenTofu and author of Terraform Up and Running
He is a brilliant engineer who truly cares about his code and the people who use it. He has the remarkable ability to pick apart hard problems (technical or otherwise) and put together a solution that benefits everyone.
Sachin Fernandes
Sachin Fernandes
Technical Lead at Cloudflare
Zack thinks fast, adapts to shifting requirements, and has proven he can quickly ramp up on the latest technologies to put them to good use.
Steven Fusco
Steven Fusco
Senior Engineering Manager at Kryptowire
Zack was clearly the most talented, skilled and hard working developer in his team. I frequently tapped his brain for technical questions and he was always there to help.
Christian Paulus
Christian Paulus
VP Product Marketing at Cohesity
Zack helped us build web applications for our cancer clinical trial research studies. He was a pleasure to work with, I frequently come back to ask his advice on our other web development projects.
Tom Luechtefeld
Tom Luechtefeld
CEO at Insilica
When challenging ideas were presented, Zack would jump at the opportunity to learn without any hint of hesitation to take on difficulty.
Anthony Davanzo
Anthony Davanzo
Technical Product Marketing Manager at HashiCorp

Tutorial: Build a RAG pipeline with LangChain, OpenAI and Pinecone

Get everything you need to build production-ready RAG applications: a step-by-step tutorial, ready-to-use Jupyter notebook for data processing, and a complete Next.js example site. Perfect for developers who want to add the most in-demand Gen AI skill to their toolkit.

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Author

Zachary Proser - full stack developer

Hi, I'm Zachary Proser

I'm a software engineer with over 13 years of experience building production systems.

WorkOSDeveloper Education
2024Present
Pinecone.ioStaff Developer Advocate
20232024
Gruntwork.ioTech Lead
20202023
CloudflareSenior Software Engineer
20172020
CloudmarkSoftware Engineer
20152017
BrightContextSoftware Engineer
20122014