ColiVara indexes documents by generating visual embeddings using vision models rather than traditional text chunking or OCR. This approach handles complex document layouts without broken tables or missing images. It provides Python and TypeScript SDKs for document upload, semantic retrieval, and collection management, targeting state-of-the-art retrieval performance for both text-heavy and visual documents.