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
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
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.
Getting Started
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.
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”
“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.”
“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.”
“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.”
“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.”
“When challenging ideas were presented, Zack would jump at the opportunity to learn without any hint of hesitation to take on difficulty.”
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
Hi, I'm Zachary Proser
I'm a software engineer with over 13 years of experience building production systems.
