+
+

Related Products

  • Gemini Enterprise Agent Platform
    999 Ratings
    Visit Website
  • LM-Kit.NET
    29 Ratings
    Visit Website
  • LTX
    182 Ratings
    Visit Website
  • Runpod
    230 Ratings
    Visit Website
  • Bright Data
    1,424 Ratings
    Visit Website
  • LogicalDOC
    150 Ratings
    Visit Website
  • Intellimas
    30 Ratings
    Visit Website
  • PackageX OCR Scanning
    48 Ratings
    Visit Website
  • Adaptive Security
    91 Ratings
    Visit Website
  • Gaffa
    5 Ratings
    Visit Website

About

NVIDIA NeMo Retriever is a collection of microservices for building multimodal extraction, reranking, and embedding pipelines with high accuracy and maximum data privacy. It delivers quick, context-aware responses for AI applications like advanced retrieval-augmented generation (RAG) and agentic AI workflows. As part of the NVIDIA NeMo platform and built with NVIDIA NIM, NeMo Retriever allows developers to flexibly leverage these microservices to connect AI applications to large enterprise datasets wherever they reside and fine-tune them to align with specific use cases. NeMo Retriever provides components for building data extraction and information retrieval pipelines. The pipeline extracts structured and unstructured data (e.g., text, charts, tables), converts it to text, and filters out duplicates. A NeMo Retriever embedding NIM converts the chunks into embeddings and stores them in a vector database, accelerated by NVIDIA cuVS, for enhanced performance and speed of indexing.

About

VectorDB is a lightweight Python package for storing and retrieving text using chunking, embedding, and vector search techniques. It provides an easy-to-use interface for saving, searching, and managing textual data with associated metadata and is designed for use cases where low latency is essential. Vector search and embeddings are essential when working with large language models because they enable efficient and accurate retrieval of relevant information from massive datasets. By converting text into high-dimensional vectors, these techniques allow for quick comparisons and searches, even when dealing with millions of documents. This makes it possible to find the most relevant results in a fraction of the time it would take using traditional text-based search methods. Additionally, embeddings capture the semantic meaning of the text, which helps improve the quality of the search results and enables more advanced natural language processing tasks.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Enterprise developers and data scientists searching for a tool to build scalable, high-accuracy AI applications

Audience

Anyone in need of a tool to save, search, store, manage, and retrieve text

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

NVIDIA
Founded: 1993
United States
developer.nvidia.com/nemo-retriever

Company Information

VectorDB
United States
vectordb.com

Alternatives

Alternatives

NVIDIA NeMo

NVIDIA NeMo

NVIDIA

Categories

Categories

Integrations

Lamatic.ai
NVIDIA NIM
NVIDIA NeMo
Python

Integrations

Lamatic.ai
NVIDIA NIM
NVIDIA NeMo
Python
Claim NVIDIA NeMo Retriever and update features and information
Claim NVIDIA NeMo Retriever and update features and information
Claim VectorDB and update features and information
Claim VectorDB and update features and information