For years, giving your website the ability to answer customer questions in plain language often meant significant development work or outsourcing to a conversational AI vendor. Both paths had drawbacks, from rigid, rules-based systems to limited control and high costs. As consumers increasingly turn to AI-powered search tools, their expectations have shifted. Many no longer want to click through menus or search for keywords; they want to ask the web a question and receive a relevant, context-aware answer. 

Microsoft’s new open-source project, NLWeb, offers a fundamental change. It aims to enable any website to respond to natural language queries directly and intelligently, using open standards, structured data, and your choice of AI models. Just as HTML transformed the web into a linked document space, NLWeb could help turn it into a conversational one. 

The Need for NLWeb Now 

The emergence of Large Language Models (LLMs) has changed what’s possible. Natural language interfaces are no longer a niche feature; they’re becoming essential. NLWeb lowers the barrier for website owners, developers, and businesses by providing an open protocol for asking websites questions in natural language. This creates a common language for interaction. It also offers a semantic response format using Schema.org standards, ensuring answers are not just human-readable but also machine-interpretable, which enables further automation and integration. Finally, NLWeb provides a lightweight, modular reference implementation that you can run on anything from a laptop to a cloud cluster, offering flexibility and scalability. 

Instead of locking teams into a specific vendor’s technology, NLWeb promotes portability and extensibility. It’s not trying to be the “one true chatbot”; it provides the tools to build your own conversational front-end using data you already have. 

How NLWeb Works 

NLWeb is built around two core components. First, there’s the protocol. It uses a REST-based endpoint that receives natural language queries and returns structured responses in Schema.org JSON. This “ask” endpoint uses MCP (Model Context Protocol), a new standard designed to help LLM agents interact with external tools, similar to how HTTP allows browsers to communicate with servers. 

Second is the implementation. This is a reference application that indexes semi-structured content (like recipes, product listings, or blog posts) from Schema.org or RSS feeds into a vector database. When a user asks a question, NLWeb retrieves the most relevant entries and uses them to construct a prompt for the LLM you choose. 

While there’s a basic web user interface for testing, the project encourages using your own frontend for production deployments or embedding the functionality into existing interfaces. 

Significance for Businesses 

For digital product owners, content teams, and web developers, NLWeb provides a practical path forward that is both compliant with standards and ready for the future. You can expect faster development since you won’t need an entire AI engineering team to build natural language interfaces, which reduces the time it takes to deliver value. Businesses also get to control their technology, using their own data, their preferred vector database, and their chosen LLM, maintaining full control over their technology stack.  

This also means your content is always up-to-date, as you connect directly to your live website content, avoiding the problem of stale information or cumbersome content exports from your CMS. Ultimately, this helps you future-proof experiences, aligning your website towards conversational and agent-driven interactions. 

Businesses can start by enabling NLWeb endpoints for specific content areas, such as knowledge bases, product catalogs, or learning centers. From there, they can expand into more complex workflows like agent orchestration, personalized recommendations, or voice-driven navigation. 

A Collaborative Approach 

NLWeb is not a finished product. It’s a foundational blueprint and an invitation to participate. As Microsoft notes, this project is about “shared protocols, sample implementations, and community participation.” Just as HTML unlocked document sharing, NLWeb offers a conversational layer for the AI-powered internet. Whether you’re building for your customers, your agents, or your future AI assistants, NLWeb is a project worth watching and potentially adopting. 

Categories: Conversational Intelligence, Intelligent Assistants, Articles