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Average Ratings 0 Ratings
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
Ragie simplifies the processes of data ingestion, chunking, and multimodal indexing for both structured and unstructured data. By establishing direct connections to your data sources, you can maintain a consistently updated data pipeline. Its advanced built-in features, such as LLM re-ranking, summary indexing, entity extraction, and flexible filtering, facilitate the implementation of cutting-edge generative AI solutions. You can seamlessly integrate with widely used data sources, including Google Drive, Notion, and Confluence, among others. The automatic synchronization feature ensures your data remains current, providing your application with precise and trustworthy information. Ragie’s connectors make integrating your data into your AI application exceedingly straightforward, allowing you to access it from its original location with just a few clicks. The initial phase in a Retrieval-Augmented Generation (RAG) pipeline involves ingesting the pertinent data. You can effortlessly upload files directly using Ragie’s user-friendly APIs, paving the way for streamlined data management and analysis. This approach not only enhances efficiency but also empowers users to leverage their data more effectively.
API Access
Has API
No
API Access
Has API
Yes
Integrations
Azure AI Services
Yes
Azure Machine Learning
Yes
Azure Marketplace
Yes
Azure OpenAI Service
Yes
Cognee
Yes
Confluence
No
Google Drive
No
Microsoft Azure
Yes
Microsoft Copilot Studio
Yes
Microsoft Foundry Agent Service
Yes
Integrations
Azure AI Services
No
Azure Machine Learning
No
Azure Marketplace
No
Azure OpenAI Service
No
Cognee
No
Confluence
Yes
Google Drive
Yes
Microsoft Azure
No
Microsoft Copilot Studio
No
Microsoft Foundry Agent Service
No
Pricing Details
$0.11 per hour
Free Trial
Yes
Free Version
Yes
Pricing Details
$500 per month
Free Trial
Yes
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
Yes
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
Yes
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
No
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
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
Ragie
Founded
2024
Website
www.ragie.ai/
Product Features
Enterprise Search
AI / Machine Learning
No
Faceted Search / Filtering
No
Full Text Search
No
Fuzzy Search
No
Indexing
No
Text Analytics
No
eDiscovery
No