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About
Neum AI is a best-in-class framework to build your data infrastructure for Retrieval Augmented Generation (RAG) and Semantic Search. It provides a collection of connectors to help you quickly spin up data pipelines that take your existing unstructured and structured data and converts it into vector embeddings ready to be used to generate search indexes. Neum AI then helps you scale up your pipeline to process millions of vectors through its managed platform as well as keeping all the vectors up to date.
Key features
- Versatile data connectors
- Data to vector embedding conversion
- Managed platform for large-scale processing
- Up-to-date embedding maintenance
- Optimized for RAG and semantic search
- Quickly deployable data pipelines
Use cases
- Building intelligent chatbots
- Enhancing enterprise internal search
- Developing Q&A applications
- Advanced sentiment analysis
Frequently asked questions
What is Neum AI and what is it used for?
Neum AI is a framework for building data infrastructures for Retrieval Augmented Generation (RAG) and Semantic Search. It converts your data into vector embeddings for enhanced search and content generation.
How does Neum AI handle structured and unstructured data?
Neum AI provides connectors to ingest various data types, whether structured or unstructured, and converts them into usable vector embeddings.
Can Neum AI's platform handle large volumes of data?
Yes, Neum AI is designed to scale your pipeline to process millions of vectors through its managed platform, ensuring optimal performance.
Who is it for?
This tool can be useful for:
- AI Developers
- Data Engineers
- Solutions Architects
- Product Managers
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