UnTXT
Be Original Again
Origins
UnTXT grew out of the work behind CVaaS. AI-generated applications became so common that employers started rejecting mass submissions without reading them, and that is when the real problem showed itself: people had stopped trusting their own voice, or lost the confidence to use it. Same story in coursework, in professional writing, and in messages from people who never touched an AI tool and got flagged anyway.
Existing detection tools made the problem worse. A single percentage score or a binary verdict doesn't tell a writer what to fix or why it was flagged. It just creates anxiety. UnTXT was built to do the opposite: surface specific patterns, explain them, and give writers something they could actually act on.
The Solution
UnTXT analyses submitted text and highlights passages that match patterns associated with AI-generated writing. Rather than producing a score or a verdict, it returns colour-coded, passage-level annotations showing which specific sentences triggered which detection modules and why.
UnTXT is built as a tool for writers, not a tribunal. It surfaces patterns so authors can decide how to revise — it doesn't rule on authorship. Early testing backed that up: users kept asking for more detail, because they wanted to learn from the output, not just clear a check.
What people say
“The tutorial is super straightforward and clear, the website isn’t overwhelming… I know this will help a lot of neurodivergent students who struggle with unclear instructions and what is ‘expected’.”
“I've tried several AI detection tools, and UnTXT — AI Detector & Writing Checker stands out because it provides detailed, sentence-level feedback instead of just a single AI score. The Chrome extension is lightweight, easy to use, and gives quick results. I appreciate how it helps improve writing rather than simply labeling it. Definitely a valuable productivity tool.”
Detection Approach
UnTXT uses 11 named detection modules. Each module identifies a different class of signal (structural, lexical, stylistic, or rhetorical) that is associated with AI-generated writing patterns. A passage may be flagged by one or more modules; each flag is labelled and colour-coded.
These are signal categories, not absolute indicators. A flag does not confirm AI generation; it highlights a pattern that warrants attention.
SPIKE
Identifies abrupt changes in language register or complexity
SYNTAX
Flags structural sentence patterns common in AI-generated text
FORMAL
Detects overly formal or clinical phrasing atypical for the author
HUMAN
Assesses absence of natural human writing markers
TEMPLATE
Identifies generic structural patterns and filler phrases
FRONTED
Detects fronted adverbials and clause structures characteristic of AI output
FORENSIC
Applies deeper lexical and stylistic forensic analysis
RHETORIC
Identifies rhetorical structures frequently used by language models
PUFF
Flags meaningless amplifying language and superlatives
FORMULA
Detects formulaic construction patterns across paragraphs
LEXICAL
Analyses vocabulary choice patterns associated with AI generation
Key Features
- Passage-level colour-coded annotations; not a percentage score
- 11 named detection modules covering structural, lexical, and rhetorical signals
- Academic mode optimised for essay submissions
- Freemium model: first 5,000 words analysed free, no card required
- Role-based entry for students, teachers, and professionals
Target Users
Students
Review drafts before submission to identify AI-pattern passages and revise for authentic voice
Teachers
Assess submitted work and open conversation with students about writing authenticity
Professionals
Review written deliverables (reports, proposals, communications) for AI writing signals before publication
Pricing
The first 5,000 words are analysed free with no card required. Premium tiers are available for higher usage. Sign-in unlocks bonus word allocation.