Tensor-based vector search that indexes images and text out of the box. Multimodal retrieval at scale.
Marqo removes the embedding pipeline from vector search. Hand it raw text or images and it generates vectors, indexes them, and serves hybrid (lexical + tensor) search through one API — ideal for e-commerce and RAG.
Who it's for: Engineering teams building search or RAG over text and images who want embeddings handled for them.
Marqo generates embeddings internally — pass raw text or images, it handles tokenization and vectors.
One engine searches across text and images using the same API, ideal for e-commerce and RAG.
Combines lexical and vector signals for relevance that beats pure ANN in many cases.
Run on Marqo Cloud or your own Kubernetes with sharding and replication.
Marqo is the fastest path to multimodal search if you do not want to babysit an embedding pipeline. For text-and-image RAG it is a standout. Once you outgrow the OSS defaults, Marqo Cloud keeps the ops off your plate.