NeumAI is an AI Agents & Automation tool that helps developers manage the creation and synchronization of vector embeddings at scale. It provides a comprehensive solution for Retrieval Augmented Generation (RAG) with built-in data connectors and real-time synchronization.
NeumAI is a robust data platform designed to empower developers in leveraging their data for contextualizing Large Language Models (LLMs) through Retrieval Augmented Generation (RAG). It streamlines the process of extracting data from various sources, including document storage and NoSQL databases, processing this content into vector embeddings, and then ingesting these embeddings into vector databases for efficient similarity search. The platform offers a high-throughput, distributed architecture capable of handling billions of data points, ensuring optimal parallelization for embedding generation and ingestion. Key features include built-in connectors for common data sources, embedding services, and vector stores, along with real-time data synchronization. NeumAI also provides customizable data pre-processing options and cohesive data management to support hybrid retrieval with augmented metadata, reducing the time spent on integrating diverse services.
Best used for
Ideal for developers and data scientists who need to build scalable Retrieval Augmented Generation (RAG) applications, synchronize diverse data sources for LLMs, and manage vector embeddings efficiently. Especially valuable for those requiring high-throughput data processing and real-time updates for their AI applications.
Common actions
manage vector embeddings
synchronize data sources
build RAG pipelines
process data for LLMs
integrate vector databases
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Capabilities
Key features
Vector embedding management
Real-time data synchronization
Built-in data connectors
Customizable data pre-processing
Distributed architecture
Metadata augmentation
Target Audience
developerdata scientistproduct manager
Integrations
openaiweaviateqdrantpineconesupabases3azure-blob-storagesharepoint+ 1 more
Pricing & Plans
Likely Not Free · Enterprise
Free
FAQs
What data sources can NeumAI connect to?
NeumAI offers built-in connectors for various data sources including Postgres, hosted files, websites, S3, Azure Blob Storage, Sharepoint, and Singlestore. It also supports embedding services like OpenAI and Azure OpenAI, and integrates with vector stores such as Weaviate, Qdrant, Pinecone, and Supabase.
Can I self-host NeumAI?
Yes, NeumAI offers self-hosting options. If you are interested in deploying NeumAI to your own cloud environment, you can contact their team at founders@tryneum.com for more information and a sample backend architecture to get started.
How does NeumAI handle data synchronization?
NeumAI provides real-time synchronization of data sources. This feature ensures that your data remains consistently up-to-date within your vector databases, which is crucial for maintaining the accuracy and relevance of your Retrieval Augmented Generation (RAG) applications.
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