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Average Ratings 0 Ratings

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ease
features
design
support

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Description

Experience the power of localized and secure AI right on your desktop, providing you with in-depth insights while maintaining complete data security and privacy. Our innovative macOS-native application combines efficiency, privacy, and intelligence through its state-of-the-art AI functionalities. The RAG system is capable of tapping into data from a local knowledge base to enhance the capabilities of the large language model (LLM), allowing you to keep sensitive information on-site while improving the quality of responses generated by the model. To set up RAG locally, you begin by breaking down documents into smaller segments, encoding these segments into vectors, and storing them in a vector database for future use. This vectorized information will play a crucial role during retrieval operations. When a user submits a query, the system fetches the most pertinent segments from the local knowledge base, combining them with the original query to formulate an accurate response using the LLM. Additionally, we are pleased to offer individual users lifetime free access to our application. By prioritizing user privacy and data security, our solution stands out in a crowded market.

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

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Codestral
Confluence
Google Drive
Hugging Face
Llama
Llama 2
Llama 3.1
Llama 3.2
Llama 3.3
Mathstral
Microsoft PowerPoint
Ministral 3B
Mistral 7B
Mistral AI
Mistral Large
Mistral Small
Mixtral 8x7B
Notion
OpenAI
Swift

Integrations

Codestral
Confluence
Google Drive
Hugging Face
Llama
Llama 2
Llama 3.1
Llama 3.2
Llama 3.3
Mathstral
Microsoft PowerPoint
Ministral 3B
Mistral 7B
Mistral AI
Mistral Large
Mistral Small
Mixtral 8x7B
Notion
OpenAI
Swift

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

$500 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

Klee

Website

kleedesktop.com

Vendor Details

Company Name

Ragie

Founded

2024

Website

www.ragie.ai/

Product Features

Artificial Intelligence

Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)

Alternatives

Alternatives

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