About Neum AI

Neum AI provides an open-source framework for building scalable Retrieval-Augmented Generation (RAG) pipelines, enabling developers to efficiently manage data flows and real-time synchronization with vector databases. This technology addresses the challenge of integrating and embedding large-scale data into AI applications, ensuring high performance and reliability.

```xml <problem> Building Retrieval-Augmented Generation (RAG) pipelines for AI applications requires significant effort in data integration, transformation, and synchronization with vector databases, especially when dealing with large-scale, real-time data. Existing solutions often lack the scalability and real-time capabilities needed to maintain up-to-date context for AI models. </problem> <solution> Neum AI offers an open-source framework designed to streamline the creation and management of scalable RAG pipelines. The framework provides tools for composing data flows, built-in connectors to various data sources, embedding models, and vector databases. It enables developers to efficiently load, chunk, embed, and synchronize data, ensuring AI applications have access to the most current information. Neum AI also offers a production-ready cloud platform for deploying and monitoring these pipelines, featuring a distributed architecture optimized for large-scale data processing, real-time syncing, and smart retrieval capabilities. </solution> <features> - Open-source SDKs for composing data flows and building RAG pipelines - Built-in connectors for data sources, embedding models, and vector databases - Production-ready cloud platform for deploying and scaling RAG pipelines - Distributed architecture optimized for embedding generation and ingestion of billions of data points - Built-in pipeline scheduling and real-time syncing to keep vectors up-to-date - Observability tools to monitor data synchronization and pipeline performance - Smart retrieval informed by data organization and metadata - Tools for testing, evaluating, and comparing different pipeline configurations </features> <target_audience> Neum AI targets AI developers and data scientists who need to build and deploy scalable, real-time RAG pipelines for their AI applications. </target_audience> <revenue_model> Neum AI offers a tiered pricing model, including a free tier with limited scale and paid plans that provide unlimited scale, access to pipeline scheduling and real-time syncing, and dedicated support. </revenue_model> ```

What does Neum AI do?

Where is Neum AI located?

Neum AI is based in Seattle, United States.

When was Neum AI founded?

Neum AI was founded in 2023.

Location

Seattle, United States

Founded

2023

Employees

7 employees

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Neum AI

Score: 90/100

AI-Generated Company Overview (experimental) – could contain errors

Executive Summary

neum.ai 1K+

Founded 2023 – Seattle, United States

Funding

No funding information available. Click "Fetch funding" to run a targeted funding scan.

Team (5+)

Pinhas Cohen

Building the Veterinarian's best friend

David de Matheu

Building the veterinarians best friend at VetRec (YC S23)

Sanath Nagaraj

Founding Engineer

Company Description

Problem

Building Retrieval-Augmented Generation (RAG) pipelines for AI applications requires significant effort in data integration, transformation, and synchronization with vector databases, especially when dealing with large-scale, real-time data. Existing solutions often lack the scalability and real-time capabilities needed to maintain up-to-date context for AI models.

Solution

Neum AI offers an open-source framework designed to streamline the creation and management of scalable RAG pipelines. The framework provides tools for composing data flows, built-in connectors to various data sources, embedding models, and vector databases. It enables developers to efficiently load, chunk, embed, and synchronize data, ensuring AI applications have access to the most current information. Neum AI also offers a production-ready cloud platform for deploying and monitoring these pipelines, featuring a distributed architecture optimized for large-scale data processing, real-time syncing, and smart retrieval capabilities.

Features

Open-source SDKs for composing data flows and building RAG pipelines

Built-in connectors for data sources, embedding models, and vector databases

Production-ready cloud platform for deploying and scaling RAG pipelines

Distributed architecture optimized for embedding generation and ingestion of billions of data points

Built-in pipeline scheduling and real-time syncing to keep vectors up-to-date

Observability tools to monitor data synchronization and pipeline performance

Smart retrieval informed by data organization and metadata

Tools for testing, evaluating, and comparing different pipeline configurations

Target Audience

Neum AI targets AI developers and data scientists who need to build and deploy scalable, real-time RAG pipelines for their AI applications.

Revenue Model

Neum AI offers a tiered pricing model, including a free tier with limited scale and paid plans that provide unlimited scale, access to pipeline scheduling and real-time syncing, and dedicated support.