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Microsoft Unveils NLWeb Open Project to Bring AI-Powered Natural Language Interfaces to Websites

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Microsoft has unveiled a new open project called NLWeb at its Build 2025 developer conference, aimed at transforming how users interact with websites. Short for Natural Language Web, NLWeb is designed to add AI-powered natural language interfaces to websites, enabling them to understand and respond to user queries just like a conversational assistant. Microsoft believes this innovation could be as foundational to the next era of the web as HTML was to the birth of websites. By embedding this AI layer, websites can evolve into more interactive and intelligent platforms.

In its announcement, Microsoft explained that NLWeb would essentially allow websites to become AI applications. Instead of relying on traditional search bars or structured navigation, users will be able to ask questions or make requests in natural language—such as “Show me the latest pricing plans” or “Summarize this article”—and receive relevant, AI-generated responses. This capability can significantly enhance user engagement and streamline access to content.

Beyond just chat interfaces, NLWeb introduces a deeper integration into the broader AI ecosystem. Each NLWeb-enabled site also acts as a Model Context Protocol (MCP) server. MCP is an open standard, originally developed by Anthropic, that allows AI agents to access external data in a structured way. By supporting MCP, websites not only serve users directly but also make their content accessible to other AI agents and services, turning static web content into dynamic data sources.

Microsoft emphasized that NLWeb is fully open-source and available to developers starting today. Hosted on GitHub and integrated with the Azure AI Foundry Labs, the platform invites developers, researchers, and website owners to experiment, contribute, and help shape the future of AI-native web experiences. As more websites adopt NLWeb, it could lead to a more intelligent, agent-compatible internet where users interact naturally with the web—just like talking to an assistant.

Zoom Enhances Agentic Tools with AI-Powered Companion, Zoom Tasks, and Additional Features

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Zoom Unveils New AI-Driven Tools to Enhance Enterprise Productivity

Zoom has unveiled a suite of new features aimed at expanding its agentic capabilities for enterprise users. Last week, the company introduced several AI-powered tools designed to streamline workflows within the Zoom Workplace ecosystem. Among these are the Custom AI Companion, Zoom Tasks, and a host of updates to existing products like Zoom Phone, Whiteboard, and Zoom CX. These innovations come on the heels of Zoom’s announcement in March, where it laid out its agentic strategy and detailed the upcoming features that would enhance productivity for users.

A major addition to Zoom’s portfolio is Zoom Tasks, which integrates directly with the Zoom AI Companion. This feature allows users to detect, manage, and complete tasks across the Zoom Workplace platform. Zoom Tasks can automatically generate to-do lists from Zoom Team Chat, Mail, or Docs, and turn them into actionable items that users can either execute themselves or delegate to the AI Companion. The tasks come with insights and suggested next steps, streamlining team collaboration and productivity. A centralised task management tab allows teams to keep track of their progress, and Zoom Tasks is available to those with Zoom Workplace plans.

In addition to Zoom Tasks, Zoom has introduced Custom AI Companion for enterprise-level customers. This feature is powered by Zoom AI Studio and offers businesses a customizable version of the AI Companion. The AI Companion can connect to a variety of third-party AI agents, extending its functionality and enabling users to perform a wide range of tasks. Zoom has ensured compatibility with models like Anthropic’s Model Context Protocol (MCP) and Google’s Agent to Agent Protocol, facilitating seamless integration with external tools. This expanded AI functionality offers a more tailored and efficient experience for businesses seeking automation and enhanced capabilities.

These new AI tools are part of Zoom’s broader vision to reshape the workplace with agentic technologies. The company also rolled out updates for other Zoom services, including improvements to Zoom Meetings, Team Chat, and the Zoom Revenue Accelerator. While some of these features are available to all users, the more advanced tools like the Custom AI Companion are limited to paid users. Zoom’s latest updates aim to further solidify its position as a leading platform for business communications and productivity.

Cohere Unveils Embed 4: An AI-Driven Multimodal Search Engine for Efficient Enterprise Data Access

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Cohere has launched Embed 4, an advanced AI-powered embedding tool designed to enhance the search and retrieval capabilities for businesses developing AI applications. Released last week, the new tool is aimed at enterprises looking to improve the efficiency of their AI systems in handling complex, multimodal documents. Embed 4 is engineered to understand a broad range of document types, enabling AI models to easily retrieve the precise information needed to complete tasks. Additionally, Cohere claims that Embed 4 can help companies reduce data storage costs by using compressed embeddings rather than storing full documents.

Embed 4 offers a sophisticated multimodal approach to embedding, which allows it to seamlessly integrate with existing AI systems and provide enhanced search and retrieval functionalities. The tool is currently accessible via the Cohere website, as well as through major platforms like Microsoft Azure AI Foundry and Amazon SageMaker. This makes it easy for businesses to implement Embed 4 in their cloud infrastructure or private environments. Furthermore, businesses have the flexibility to deploy Embed 4 in virtual private clouds (VPCs) or on-premises, depending on their operational needs.

One of the key features of Embed 4 is its ability to augment traditional AI models with Retrieval-Augmented Generation (RAG) technology. RAG is a process that enables AI systems to search for and retrieve relevant information from their knowledge base in real time, based on specific keywords and algorithms. With Embed 4, this functionality is enhanced, allowing businesses to use external data sources more efficiently while maintaining the same level of precision and accuracy.

For enterprises that rely heavily on AI models for decision-making and operational efficiency, Embed 4 promises to be a valuable tool. By improving the way AI systems retrieve and process complex data, it not only accelerates tasks but also helps optimize storage and computing resources. Cohere’s Embed 4 could play a crucial role in the future of AI-powered enterprise solutions, making it easier for businesses to harness the full potential of their data while cutting down on unnecessary costs.