Indexing and searching images, audio, video, and mixed-media content.
Turn slide decks into a continuously updated multimodal dataset with CocoIndex: extract speaker notes with Gemini Vision, synthesize narration with Piper TTS, and keep LanceDB in sync.
Extract Pydantic-typed structured data from patient intake forms using DSPy and CocoIndex: OCR vision models with incremental processing.
Extract, embed, and store multimodal PDF elements (text with SentenceTransformers, images with CLIP) for unified semantic search with traceable metadata.
Build a unified visual document index from multiple file formats (including PDFs, images, and slides) using CocoIndex and ColPali. No OCR needed.
CocoIndex updates: production readiness, scalability, and reliability, plus more customization, native integrations, and multi-modal pipeline features.
CocoIndex now natively integrates ColPali for multi-vector, patch-level image indexing: multi-modal context engineering for visually rich documents and PDFs.
CocoIndex natively handles typed multi-dimensional vectors, from simple arrays to multi-vector embeddings, unlocking multimodal AI pipelines at scale.
Build a scalable face detection and recognition pipeline with CocoIndex: embed faces, structure for search, and export to a vector DB.
Indexing images with CocoIndex and Vision Model in real-time: multi-modal embedding, and build vector index for efficient retrieval.
Extract structured data from patient intake forms in PDF and Word documents using an LLM and CocoIndex: a practical healthcare document extraction example.