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Neum AI is an ETL platform for LLM data, designed to help companies connect and synchronize data into vector stores in real-time. It provides a framework to build data infrastructure for Retrieval Augmented Generation (RAG) and Semantic Search. Neum AI offers connectors to create data pipelines that convert unstructured and structured data into vector embeddings for search indexes. The platform scales to process millions of vectors and keeps them up-to-date, even as the underlying data changes.
## How to Use
Use Neum AI to connect to various data sources, transform the data into vector embeddings, store them in vector databases, and keep them synchronized. The platform offers open-source SDKs for local pipeline development and deployment to the Neum AI cloud.
Neum AI's
## Key Features
- Data connectors for various sources, embedding models, and vector databases - Open-source SDKs for composing data flows - Managed platform for scaling data pipelines - Real-time data synchronization - Built-in retrieval informed by data organization and metadata - Observability tools for monitoring data syncing - Retrieval evaluation tools
## Use Cases
- Building Retrieval Augmented Generation (RAG) pipelines - Creating semantic search indexes - Keeping chatbots up-to-date with accurate information - Real-time data embedding and indexing for RAG
## FAQ
**How can I test and deploy my pipelines?** Neum AI Discord Here is the Neum AI Discord: https://discord.gg/mJeNZYRz4m. For more Discord message, please click here(/discord/mjenzyrz4m). Neum AI
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