Noren AI: Voice Extraction Tool Identifies Writing Patterns from Samples

Noren AI is a voice extraction tool that automatically identifies writing patterns from text samples to help LLMs generate content that sounds like you. The tool was developed after the creators spent weeks manually documenting 300 lines of their own writing patterns, which they fed to Claude and other open source models to achieve voice-matching output.

How It Works

The tool takes 5 to 10 writing samples and returns a voice guide built from your actual patterns, not your guesses about yourself. When tested on the same writing samples used for manual documentation, Noren matched 90% of the manually identified patterns and found 8 more patterns the creators had completely missed about themselves.

Development Background

The project started from frustration with AI-generated content that felt technically accurate but lacked authentic voice. The team initially used Claude, Llama, ChatGPT and Qwen to draft tweets and emails, finding the output clean and structured but with a persistent "low-grade wrongness." System prompts like "Be concise. Be direct. Match my tone" helped but still felt off.

Instead of trying to describe their voice through prompts, they documented it by analyzing patterns in their writing: how sentences tend to start and end, words used when thinking fast versus being careful, recurring analogies, and argument styles. This manual process created what felt like "an accidental self-portrait" rather than a style guide.

Results

When they fed their 300-line manual guide to Claude and other open source models, the output finally sounded like them. Constant readers couldn't tell the difference between AI-generated drafts and authentic writing. The patterns identified by Noren AI weren't hallucinations—everything traced back to real sentences in actual text they had written.