RAG-first framework to build performant, scalable and reliable data pipelines. Focused on key data transformations like loading, chunking and embedding.
Choose from connectors for data sources, embedding models and vector databases. Add your own connectors using our open-source framework.
Run your data pipelines locally using open-source SDKs and directly deploy those same pipelines to the Neum AI cloud.
Distributed architecture that optimizes embedding generation and ingestion to handle billions of data points.
Keep your vectors in sync with built-in pipeline scheduling and real-time syncing.
Neum AI cohesively tracks and augments metadata to provide rich retrieval experience.
Monitor your data pipelines to ensure your data is correctly being synced into your vector database.
Built-in retrieval informed by the organization of your data and the metadata associated to it.
Improve context quality by providing feedback on retrieval quality.