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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Achieve exceptional response quality through a vector database specifically designed for advanced retrieval augmented generation (RAG) and contemporary search functionalities. Emphasize substantial growth with a robust, enterprise-ready vector database that inherently includes security, compliance, and ethical AI methodologies. Create superior applications utilizing advanced retrieval techniques that are underpinned by years of research and proven customer success. Effortlessly launch your generative AI application with integrated platforms and data sources, including seamless connections to AI models and frameworks. Facilitate the automatic data upload from an extensive array of compatible Azure and third-party sources. Enhance vector data processing with comprehensive features for extraction, chunking, enrichment, and vectorization, all streamlined in a single workflow. Offer support for diverse vector types, hybrid models, multilingual capabilities, and metadata filtering. Go beyond simple vector searches by incorporating keyword match scoring, reranking, geospatial search capabilities, and autocomplete features. This holistic approach ensures that your applications can meet a wide range of user needs and adapt to evolving demands.

Description

While generative AI is a relatively recent development, our efforts over the last five years have paved the way for this moment. Deep Lake merges the strengths of data lakes and vector databases to craft and enhance enterprise-level solutions powered by large language models, allowing for continual refinement. However, vector search alone does not address retrieval challenges; a serverless query system is necessary for handling multi-modal data that includes embeddings and metadata. You can perform filtering, searching, and much more from either the cloud or your local machine. This platform enables you to visualize and comprehend your data alongside its embeddings, while also allowing you to monitor and compare different versions over time to enhance both your dataset and model. Successful enterprises are not solely reliant on OpenAI APIs, as it is essential to fine-tune your large language models using your own data. Streamlining data efficiently from remote storage to GPUs during model training is crucial. Additionally, Deep Lake datasets can be visualized directly in your web browser or within a Jupyter Notebook interface. You can quickly access various versions of your data, create new datasets through on-the-fly queries, and seamlessly stream them into frameworks like PyTorch or TensorFlow, thus enriching your data processing capabilities. This ensures that users have the flexibility and tools needed to optimize their AI-driven projects effectively.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon SageMaker
Amazon Web Services (AWS)
Azure AI Foundry Agent Service
Azure AI Services
Azure Machine Learning
Azure Marketplace
Azure OpenAI Service
ChatGPT
Cognee
Google Cloud Platform
Jupyter Notebook
LangChain
Microsoft Azure
Microsoft Copilot Studio
Microsoft Intelligent Data Platform
OpenAI
PyTorch
TensorFlow
Titan CMS

Integrations

Amazon SageMaker
Amazon Web Services (AWS)
Azure AI Foundry Agent Service
Azure AI Services
Azure Machine Learning
Azure Marketplace
Azure OpenAI Service
ChatGPT
Cognee
Google Cloud Platform
Jupyter Notebook
LangChain
Microsoft Azure
Microsoft Copilot Studio
Microsoft Intelligent Data Platform
OpenAI
PyTorch
TensorFlow
Titan CMS

Pricing Details

$0.11 per hour
Free Trial
Free Version

Pricing Details

$995 per month
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

Microsoft

Founded

1975

Country

United States

Website

azure.microsoft.com/en-us/products/ai-services/ai-search/

Vendor Details

Company Name

activeloop

Country

United States

Website

www.activeloop.ai/

Product Features

Enterprise Search

AI / Machine Learning
Faceted Search / Filtering
Full Text Search
Fuzzy Search
Indexing
Text Analytics
eDiscovery

Product Features

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