Neum AI is a Data & Analytics tool that provides an open-source framework for building Retrieval Augmented Generation (RAG) and semantic search data pipelines. It helps convert unstructured and structured data into vector embeddings for AI applications.
Neum AI offers a best-in-class, open-source framework designed to build robust data infrastructure for Retrieval Augmented Generation (RAG) and Semantic Search. It provides a collection of connectors to quickly set up data pipelines, transforming existing unstructured and structured data into vector embeddings. These embeddings are then ready to be used for generating search indexes. Neum AI's managed platform scales pipelines to process millions of vectors and ensures they remain up-to-date even as underlying data changes. The platform features open-source SDKs for composing data flows, built-in connectors for various data sources, embedding models, and vector databases, and tools for testing and deploying pipelines locally or to the cloud. It emphasizes scalability, real-time synchronization, observability, smart retrieval, and self-improving context quality.
Best used for
Ideal for developers and data scientists who need to build scalable and real-time Retrieval Augmented Generation (RAG) applications, generate vector embeddings from diverse data sources, and keep their vector databases synchronized. Especially valuable for those requiring an open-source framework with robust connectors and managed cloud deployment.
Common actions
build RAG pipelines
generate vector embeddings
sync real-time data
scale data infrastructure
manage data pipelines
open-sourceRAGdistributed architecturemonitoringretrieval-augmented generationdata sourcesembedding modelsvector databasesdata pipelines"Real-Time Data"+ 5 more
What types of data can Neum AI process for vector embeddings?
Neum AI is designed to process both unstructured and structured data. It converts this diverse data into vector embeddings, which are then used to build search indexes and power Retrieval Augmented Generation (RAG) applications, providing context for AI models.
Does Neum AI support real-time data synchronization?
Yes, Neum AI offers built-in pipeline scheduling and real-time syncing capabilities. This ensures that your vector embeddings remain up-to-date, even as the underlying data sources change, which is crucial for dynamic AI applications.
What is included in Neum AI's free Starter plan?
The Starter plan allows users to integrate data into their projects, providing access to open-source connectors and tools. It supports deploying pipelines to the cloud with limited scale and includes Discord access for community support.
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