Implementation Guides
Step-by-step guides for building production-ready AI applications with Pixeltable. From video analysis to RAG pipelines.
Declarative AI Infrastructure: Define Pipelines, Not Plumbing
Replace thousands of lines of orchestration code with declarative computed columns. Pixeltable handles execution, dependencies, caching, and incremental updates automatically.
Incremental Updates: Save 70% on AI Compute Costs
Stop reprocessing entire datasets when one row changes. Pixeltable tracks dependencies and recomputes only what's necessary — saving compute, time, and money.
Video Intelligence Pipeline: Extract, Enrich, and Search Video at Scale
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.
Production RAG: From Documents to Answers in One System
Build a complete Retrieval-Augmented Generation pipeline with Pixeltable. Ingest documents, chunk text, generate embeddings, index for retrieval, and generate LLM answers — no vector database or orchestrator required.
Computer Vision Pipeline: Object Detection, Classification, and Search
Build optimized computer vision workflows with Pixeltable. Run YOLOX, CLIP, and custom models as computed columns with automatic batching, caching, and incremental processing.
AI Agents & MCP: Give Your Agents Persistent Multimodal Memory
Build AI agents with durable memory and tool-calling capabilities using Pixeltable and Model Context Protocol (MCP). Store conversations, images, and documents as queryable tables that agents can read from and write to.
Multimodal AI Apps: Process Any Data Type in One System
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.
RAG at Scale: Document Processing, Embeddings, and LLM Generation
Build enterprise-grade RAG systems that handle millions of documents with automatic chunking, embedding synchronization, and LLM-powered answer generation.
Audio Transcription Pipeline with OpenAI Whisper
Transcribe audio files at scale with Pixeltable and OpenAI Whisper. Automatic batching, error handling, and incremental processing.