Marqo
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About
Marqo is an end-to-end vector search platform that enables developers to build powerful search applications and transform their retrieval stack. It offers a cloud-based solution and an open-source engine, supporting various use cases like multimodal search, e-commerce, recommendations, retrieval augmented generation (RAG), and classification. Marqo allows training and deployment of embedding models, including fine-tuning, and provides tools for embedding generation, scalable retrieval with metadata handling, and performance evaluation. It is used by diverse companies ranging from startups to large enterprises.
Platform
Task
Features
• access control
• fully managed
• high availability
• scale at the click of a button
• cpu instances and gpu instances
• model customization
• horizontally scalable
• end-to-end vector creation and storage
FAQs
What is vector search?
Vector search allows you to search documents, images and other data by converting items into a collection of vectors. This collection of vectors summarises the data in semantic form and allows us not only to match documents against queries through analysis of the semantic content, but also to understand where and how the document matched the query. With Marqo, inference to create the vectors is included.
What is the best setup for my application?
The number of instances you will need depends on a number of factors. The number of documents, the size of the documents and the type of data (image vs text). When dealing with low search volumes that primarily involve text or when low latency is not crucial, using CPU inference nodes can be a cost-effective solution. On the other hand, GPU inference nodes provide a significant performance boost when indexing and searching with images and are recommended for indexing large datasets and processing high volume, low latency searches. For multimodal models marqo.CPU.large is recommended as a minimum. The estimates for storage capacity provided in our calculator assume your are using a model that produces 768 dim. vectors.
Do I have to change my code to move from open-source to cloud?
The only changes you need to make are to update your URL and API key when accessing Marqo.
How does billing work?
You will be billed at the end of the month for total inference and shard hours used. Usage is rounded up to 15-minute increments.
Pricing Plans
Cloud
USD0.38 / per hour• Fully managed
• End-to-end vector creation and storage
• Horizontally scalable
• Model Customization
• CPU instances and GPU instances
• Scale at the click of a button
• Access control
• High availability
• Low latency
Enterprise
Unknown Price• All the functionality of Marqo Cloud
• SSO
• Single tenant deployment
• Observability Integrations
• 24/7/365 dedicated support
• Migration assistance
• Access to ML scientists
• VPC deployment (+add on)
• Enhanced Enterprise SLA
• Sizing assistance
Marqtune
Unknown Price• Fine-tune embedding models
• Generalized Contrastive Learning
• Flexible training datasets
• Wide range of base models
• Train with historical sales data
• Model evaluation
• Access to ML scientists
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