Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Deeplake is an AI data runtime and GPU database built for teams developing agents, RAG systems, multimodal applications, robotics workflows, and generative media products. It is designed to solve the gap between GPU-powered AI models and CPU-bound data systems by keeping data closer to where AI workloads execute. The platform supports serverless Postgres, vector search, multimodal data storage, analytical workloads, and AI-optimized data lake functionality. Deeplake helps agents remember, retrieve, and act in fast cycles, making it useful for systems that need repeated context retrieval across long-running tasks. It can manage complex data such as video, images, point clouds, sensors, PDFs, audio, embeddings, model weights, and structured records. Developers can use familiar database concepts while gaining support for GPU-speed retrieval and scalable AI data operations. The platform is positioned for production-grade AI use cases where agents may generate databases, query thousands of times, and require faster memory access. Deeplake also supports private deployment patterns, including VPC environments, so organizations can keep sensitive data within their own infrastructure. With open-source adoption, enterprise security credentials, and a focus on agentic workloads, Deeplake helps AI teams build faster and more efficient data systems.
Description
NVIDIA NeMo Retriever is a suite of microservices designed for creating high-accuracy multimodal extraction, reranking, and embedding workflows while ensuring maximum data privacy. It enables rapid, contextually relevant responses for AI applications, including sophisticated retrieval-augmented generation (RAG) and agentic AI processes. Integrated within the NVIDIA NeMo ecosystem and utilizing NVIDIA NIM, NeMo Retriever empowers developers to seamlessly employ these microservices, connecting AI applications to extensive enterprise datasets regardless of their location, while also allowing for tailored adjustments to meet particular needs. This toolset includes essential components for constructing data extraction and information retrieval pipelines, adeptly extracting both structured and unstructured data, such as text, charts, and tables, transforming it into text format, and effectively removing duplicates. Furthermore, a NeMo Retriever embedding NIM processes these data segments into embeddings and stores them in a highly efficient vector database, optimized by NVIDIA cuVS to ensure faster performance and indexing capabilities, ultimately enhancing the overall user experience and operational efficiency. This comprehensive approach allows organizations to harness the full potential of their data while maintaining a strong focus on privacy and precision.
API Access
Has API
API Access
Has API
Integrations
Amazon SageMaker
Amazon Web Services (AWS)
ChatGPT
Google Cloud Platform
Jupyter Notebook
LangChain
NVIDIA NIM
NVIDIA NeMo
OpenAI
PyTorch
Integrations
Amazon SageMaker
Amazon Web Services (AWS)
ChatGPT
Google Cloud Platform
Jupyter Notebook
LangChain
NVIDIA NIM
NVIDIA NeMo
OpenAI
PyTorch
Pricing Details
$0
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Activeloop
Founded
2018
Country
United States
Website
deeplake.ai/
Vendor Details
Company Name
NVIDIA
Founded
1993
Country
United States
Website
developer.nvidia.com/nemo-retriever