--- 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