---
title: AI Starter Kit
subtitle: Resources for building AI applications with Neon Postgres
enableTableOfContents: true
updatedOn: '2025-06-04T19:40:50.197Z'
---
This guide collects resources for building AI applications with Neon Postgres. You'll find core concepts, starter applications, framework integrations, and deployment guides. Use these resources to build applications like RAG chatbots, semantic search engines, or custom AI tools.
## Getting started
Learn the fundamentals of building AI applications with Neon:
AI concepts
pgvector extension
## AI frameworks and integrations
Build AI applications faster with these popular frameworks, tools, and services:
LangChain
LlamaIndex
Semantic Kernel
Inngest
app.build
## Starter applications
Hackable, fully-featured, pre-built starter apps to get you up and running:
AI chatbot (OpenAI + LllamIndex)
AI chatbot (OpenAI + LangChain)
RAG chatbot (OpenAI + LlamaIndex)
RAG chatbot (OpenAI + LangChain)
Semantic search (OpenAI + LlamaIndex)
Semantic search (OpenAI + LangChain)
Hybrid search (OpenAI)
Reverse image search (OpenAI + LlamaIndex)
Chat with PDF (OpenAI + LlamaIndex)
Chat with PDF (OpenAI + LangChain)
## Scale your AI application
Scale with Neon
Optimize vector search
## Featured examples
Real-world AI applications built with Neon that you can reference as code examples or inspiration.
Share your AI app on our [#showcase](https://discord.gg/neon) channel on Discord.
AI vector database per tenant
Guide: Build a RAG chatbot
Guide: Build a Reverse Image Search Engine
Ask Neon Chatbot
Vercel Postgres pgvector Starter
YCombinator Semantic Search App
Web-based AI SQL Playground
Jupyter Notebook for vector search with Neon
Image search with Neon and Vertex AI
Text-to-SQL conversion with Mistral + LangChain
Postgres GPT Expert
## Vector search tools and notebooks
Optimize your vector search implementation and experiment with different approaches:
Vector search optimization
Vector search notebooks
Google Colab guide
Azure Data Studio Notebooks