Neum AI

Neum AI is an open-source framework for developers and teams building Retrieval Augmented Generation (RAG) and semantic search applications that need reliable data pipelines and vector synchronization.

Key capabilities include:

• Composable SDKs and connectors to build data flows and custom integrations, with built-in connectors for common data sources, embedding models (for example, OpenAI), and vector databases (for example, Pinecone and Weaviate).
• RAG-first transformations for turning structured and unstructured data into embeddings, including loading, chunking, embedding, preprocessing, and metadata extraction.
• Local development plus cloud deployment, so the same pipelines can run locally for testing and deploy to a managed cloud platform designed for large-scale embedding generation and ingestion.
• Operational tooling such as real-time syncing and scheduling to keep vectors up to date, plus observability, smart retrieval, feedback capture, and governance features such as role-based access controls.

Pricing: Free (Starter) and paid tiers, including Pro at $500/month, plus Enterprise (quote-based).

Notable for combining an open-source SDK with a production cloud platform focused on real-time vector sync and scaling pipelines to billions of data points, which fits teams that need RAG infrastructure beyond basic ETL scripts and one-off indexing jobs.