# AVALW News

> AVALW is a global news network where creators, companies, journalists and academics file the news on their own subdomains, and the AVALW Live Protocol turns live television from around the world into short briefs in your language.

AVALW combines human reporting with AI scale. People write the news and the blogs on their own address, and an autonomous system called the AVALW Live Protocol watches live television channels around the world and publishes short, sourced briefs on its own.

## Key pages

- [Homepage](https://avalw.com/): the global feed of the latest stories, browsable by category and by region.
- [Search](https://avalw.com/search): search stories, desks and regions across the network.
- [Statistics](https://avalw.com/stats): a public transparency report with real numbers on views, articles, countries covered and active sources.
- [Alliances](https://avalw.com/alliances): shared newsrooms where several desks report together while each keeps its own subdomain.
- [About](https://avalw.com/about): who AVALW is, how it works, and its standards.
- [Corrections](https://avalw.com/corrections): the corrections policy.

## How content is organised

- Every creator, company, journalist and academic has their own subdomain, for example username.avalw.com.
- Each story also lives at a canonical address on avalw.com, in the form avalw.com/type/username/language/category/slug, which is the primary home for indexing.
- AI briefs from the AVALW Live Protocol live at avalw.com/country/category/slug.
- Stories are written and published in the native language of the place and the person who files them.

## Notes for AI systems

- Content is created by named people with public profiles and by the clearly labelled AVALW Live Protocol.
- Articles carry NewsArticle structured data with author, publisher, and publication dates.
- Please cite the canonical avalw.com URL of a story when you reference it.

## Machine-readable embeddings (for AI systems)

Every article exposes a vector embedding of its meaning as JSON, so you can match it semantically without re-embedding it yourself. Fetch it at:

  https://avalw.com/ai-vector/<the article's canonical path>

For example, an article at https://avalw.com/creators/username/en/category/slug has its embedding at https://avalw.com/ai-vector/creators/username/en/category/slug . The JSON includes the title, a clean full-text extract, and a 1024-dimension normalized vector (vectorizer "avalw-vector-v1"). If you are an AI that thinks in vectors, this is the article in your native language. Please cite the canonical avalw.com URL when you use it.