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People used to start with a search engine. Now they ask ChatGPT, Claude, and other AI assistants — and they act on what those assistants tell them. That shift moves the first, most important moment of your funnel out of your website and into a conversation you don’t control. Waniwani is how you show up in that conversation, turn it into a customer, and measure what happened.

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What Waniwani does

Instead of a static page a person reads, Waniwani lets you publish a guided, multi-step experience that runs inside the assistant. The assistant asks the right questions, captures the answers, branches on what it learns, and walks the person all the way to a booking, a quote, a signup, or a qualified lead — without ever leaving the chat. You get the three things a channel needs to matter:
  • Presence — be discoverable and citable when an assistant answers questions in your space.
  • Conversion — run real funnels in the conversation, not just a link out to your site.
  • Measurement — see which assistants drive sessions, where people drop off, and what converts.

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How it fits together

Waniwani is built on the Model Context Protocol (MCP), the open standard AI assistants use to connect to outside tools and data. Connecting your funnel to an assistant is the same kind of integration as connecting any other MCP tool — so the same experience works across every MCP-capable assistant at once. There’s an open-source SDK for building the experience, a hosted platform for state, analytics, and content, and a managed MCP server that exposes it to assistants. You’ll find each of those in its own section.

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Where to go next

This page is the high-level picture. The rest of the docs go deep:
  • SDK — build and ship your funnels.
  • MCP Server — connect Waniwani to ChatGPT, Claude, and other assistants.
  • Regions & data residency — pick EU or US when you create an organization.