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What is Rabbit?

Modern personal computers mainly process straightforward commands rather than fully understanding complex human intentions. LAM, however, transforms natural language requests into actionable responses that the operating system can use right away. In contrast to conventional application programming interfaces (APIs), which typically have limited functionality, LAM interacts with user-centric interfaces across multiple mobile and desktop environments. Additionally, LAM goes beyond simply navigating applications to achieve particular objectives; it does so in a way that aligns with the user's experience, enhancing the intuitive and relatable nature of technology. This improvement in interaction not only facilitates a smoother incorporation of technology into everyday routines but also empowers users to engage more effectively with their devices. As a result, technology becomes an indispensable companion in navigating daily tasks.

What is NLWeb?

NLWeb represents a collaborative effort initiated by Microsoft aimed at enabling the development of a user-friendly, natural language interface for websites, employing selected models along with proprietary datasets. The initiative, abbreviated as Natural Language Web, seeks to offer a rapid and straightforward method for converting a website into an AI-driven application, thus allowing users to engage with the site's information through natural language inquiries, similar to conversing with an AI assistant or Copilot. Each NLWeb instance operates as a Model Context Protocol (MCP) server, allowing websites the opportunity to render their content discoverable and usable by various agents within the MCP ecosystem. By utilizing semi-structured data formats like Schema.org and RSS—formats that numerous websites already utilize—NLWeb merges these elements with LLM-powered solutions to create natural language interfaces that accommodate both users and AI agents, significantly improving user interaction and engagement. This forward-thinking strategy not only simplifies the integration process but also enhances the reach of web content to cater to a wider range of users, making the internet more navigable and efficient for everyone. Ultimately, NLWeb aims to revolutionize how people interact with online information by simplifying access and fostering intuitive communication.

Media

Media

Integrations Supported

Eventbrite
Inception Labs
Microsoft Copilot
Milvus
Qdrant
RSS
Schema
Shopify
Snowflake
Tripadvisor
rabbit r1

Integrations Supported

Eventbrite
Inception Labs
Microsoft Copilot
Milvus
Qdrant
RSS
Schema
Shopify
Snowflake
Tripadvisor
rabbit r1

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Rabbit

Company Website

www.rabbit.tech/

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

news.microsoft.com/source/features/company-news/introducing-nlweb-bringing-conversational-interfaces-directly-to-the-web/

Categories and 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)

Natural Language Processing

Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization

Categories and Features

Natural Language Processing

Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization

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