---
title: "AI Use Cases & Implementation Guides"
description: "Explore AI use cases and implementation guides. Learn how to build a video search engine, video analysis, document processing, and RAG with Pixeltable."
url: "https://www.pixeltable.com/use-cases"
---

# AI Use Cases & Implementation Guides

- [Video Intelligence Pipeline: Extract, Enrich, and Search Video at Scale](https://www.pixeltable.com/use-cases/video-content-analysis) - Build an end-to-end video analysis system with Pixeltable. Ingest video, extract frames, run multimodal AI models, generate embeddings, and enable semantic search, all as computed columns on a table.
- [Build a Video Search Engine in Python](https://www.pixeltable.com/use-cases/video-search-engine) - A video search engine finds a moment inside a clip, not only a filename. You sample frames or keyframes, embed them with a model such as CLIP, index those vectors, rank by similarity, and serve the query over HTTP.
- [Production RAG: From Documents to Answers in One System](https://www.pixeltable.com/use-cases/production-rag-implementation) - Build a complete Retrieval-Augmented Generation pipeline with Pixeltable. Ingest documents, chunk text, generate embeddings, index for retrieval, and generate LLM answers, with no vector database or orchestrator required.
- [Computer Vision Pipeline: Object Detection, Classification, and Search](https://www.pixeltable.com/use-cases/computer-vision-pipeline-optimization) - Build optimized computer vision workflows with Pixeltable. Run YOLOX, CLIP, and custom models as computed columns with automatic batching, stored results, and incremental processing.
- [AI Agents & MCP: Give Your Agents Persistent Multimodal Memory](https://www.pixeltable.com/use-cases/ai-agents-mcp) - Build AI agents with durable memory and tool calling using Pixeltable. Store conversations, images, and documents as queryable tables, give a Pydantic AI agent read access and a memory table, and call MCP server tools from a computed column.
- [Audio Transcription Pipeline with OpenAI Whisper](https://www.pixeltable.com/use-cases/audio-transcription-pipeline) - Transcribe audio files at scale with Pixeltable and OpenAI Whisper. Concurrent, rate-limited requests, retries, and incremental processing.
- [Declarative AI Infrastructure: Define Pipelines, Not Plumbing](https://www.pixeltable.com/use-cases/declarative-ai-data-infrastructure) - Replace thousands of lines of orchestration code with declarative computed columns. Pixeltable handles execution, dependencies, stored results, and incremental updates automatically.
- [Multimodal AI Apps: Process Any Data Type in One System](https://www.pixeltable.com/use-cases/multimodal-ai-application-development) - Build applications that work with images, videos, audio, and documents simultaneously. Pixeltable treats all modalities as first-class column types with automatic cross-modal operations.
- [Incremental Updates: Stop Reprocessing Entire Datasets](https://www.pixeltable.com/use-cases/incremental-updates-ai-data-processing) - Stop reprocessing entire datasets when one row changes. Pixeltable tracks dependencies and recomputes only what's necessary, saving compute, time, and money.
- [RAG at Scale: Document Processing, Embeddings, and LLM Generation](https://www.pixeltable.com/use-cases/retrieval-augmented-generation-systems) - Build enterprise-grade RAG systems that handle millions of documents with automatic chunking, embedding synchronization, and LLM-powered answer generation.