Embeddable chat for your site

Your site cananswerquestions.

An embeddable AI chatbot, trained only on your pages.

No redirects, no invented facts, no rewriting your voice.

01

Point it at your site

Give Axvelo your domain. It crawls your marketing pages, your docs, your changelog, your help center — anything a customer might read — and indexes it as the source of truth for every answer.

02

Shape the voice

Pick the accent color, the tone, the pages it’s allowed to live on. The widget inherits your typography and stays inside the brand you already designed. No theming gymnastics, no off-brand bubble.

03

Drop the embed

One script tag, three attributes. The widget appears on the pages you whitelisted and starts answering on day one — grounded in your content, with citations back to the source page so customers can keep reading where the answer came from.

“You already wrote the answer.
We just put it where it gets read.”

From the editors

Walkthrough

Four steps. End to end.

Crawl your site, shape the voice, try it, embed it. Here's each step up close.

01

Point us at your site.

Drop in a URL. We crawl your pages, docs, FAQs, help center — and turn them into a single source of truth.

Site URL

https://acmecorp.com
Start crawl
23 pages indexed from acmecorp.com.

02  —  Features

What you get when you ship.

  • I

    Answers from your own content

    Every reply is grounded in pages you wrote, with a citation linking back to the source. Nothing invented, nothing borrowed.

  • II

    A one-line embed

    Paste a script tag and the widget appears, styled in your brand, scoped to the domains you allow.

  • III

    Tuned to your voice

    Set the tone, the accent, the boundary of what it’ll talk about. The widget reads like your team wrote it — because, in a sense, you did.

  • IV

    Change it whenever

    Choose which pages it draws from, recolor it, and publish on your own schedule — nothing's locked in.

03  —  How it works

The architecture, end to end.

Your siteCrawlerVector DatabaseLLMAPIWidget

A question enters at the Widget, travels to the API, which retrieves the relevant chunks from the Vector Database, sends them to the LLM alongside the question, and returns a grounded answer to the Widget — with a citation linking back to the source.