Auren helps readers, educators, libraries, and organizations understand how news articles are constructed. It analyzes structural signals such as sourcing, attribution, framing, emotional language, credibility indicators, and missing context. Auren does not independently verify facts or declare claims true or false.

Lightfield — AI-native CRM that builds itself and does work for you

AI-native CRM that builds itself and does work for you

Hey everybody 👋 Auren came from one simple question: Why can two articles use the same facts and leave you feeling completely different? That bothered us. Most tools focus on whether a source is left/right, credible/not credible, or true/false. But a lot of media influence is quieter than that. It sits in the headline. In who gets quoted. In what context is missing. In which words carry emotion. In what the article makes you feel before you even notice it. So we built Auren to analyze the structure of a news article. Not to declare truth. Not to replace judgment. But to make framing, sourcing, tone, credibility signals, and missing context easier to see. The product started as a bias detector. It became a media literacy tool. We’re launching because we want feedback from people who think deeply about information, AI, news, and trust. Question: What is the biggest red flag that makes you stop trusting a news article?

Lightfield — AI-native CRM that builds itself and does work for you

AI-native CRM that builds itself and does work for you

Auren

Analyze bias, framing,emotional language,and missing context

Analyze bias, framing,emotional language,and missing context