Marqo

Open-source tensor search engine with built-in embedding and reranking

Hand-reviewed by the Toolglade team·Updated Aug 2026

vector-databases#vector-search#tensor-search#multimodal#embeddings

Free plan Claimed API Self-hosted Teams

About Marqo

Marqo is an open-source tensor search engine that generates embeddings and runs vector search in one API, built for multimodal, e-commerce-focused semantic search.

Marqo differentiates itself from pure vector databases by handling embeddings end to end: it generates embeddings and performs vector search behind one API, so teams do not have to stitch together a separate embedding pipeline, model server, and vector store. It supports reranking as well, returning results ranked by semantic similarity rather than keyword overlap. The engine is designed for multimodal search and product discovery, letting teams index text, images, and structured data together. Over time Marqo has shifted from a purely open-source project toward a managed cloud and an e-commerce-focused product suite covering AI search, recommendations, and agentic commerce. Pricing reflects that positioning: the open-source version is free to self-host, while managed and enterprise offerings are customized based on catalog size, traffic, and infrastructure. Marqo is a strong fit for retail and e-commerce teams that want semantic, multimodal search without assembling the full retrieval stack themselves.

TL;DR

Marqo is an open-source tensor search engine that unifies embedding generation and vector search in one API, focused on multimodal, e-commerce product discovery.

Company overview

Marqo builds an open-source tensor search engine and a managed cloud, increasingly focused on e-commerce search, recommendations, and agentic commerce. It positions itself as an all-in-one retrieval layer that removes the need to assemble embeddings and a vector database separately.

The company maintains an active open-source project on GitHub while commercializing through a customized enterprise cloud offering for retail and product discovery use cases.

Product features

Marqo generates embeddings and performs vector search behind a single API, with reranking and native multimodal support for text and images. This lets teams index and query heterogeneous product data semantically.

The open-source engine can be self-hosted via Docker, while Marqo Cloud adds managed infrastructure and e-commerce-oriented solutions such as AI search, recommendations, and agentic commerce.

Target market

Marqo targets retail and e-commerce teams, plus developers, who want multimodal semantic search and product discovery without building the full retrieval stack.

Buyer personas

End users

Developers building search and discovery features.

Buyers

E-commerce and product leaders investing in search relevance.

Key influencers

Search and ML engineers.

Ideal customer profile

Retail and e-commerce companies that need multimodal, semantic product search and recommendations delivered through a single managed or open-source retrieval engine.