AiRax: Rewrite & Detect AIGC in Minutes

article rewriting# AiRax: Rewrite & Detect AIGC in Minutes

What makes AiRax different from ordinary article-rewriting tools?

Unlike synonym-swappers, AiRax deploys a self-developed semantic-reconstruction engine that re-casts sentence syntax, clause order and lexical fields while locking the original argument intact. In side-by-side tests the platform cut GPT-origin traces from 87 % to 9 % and Turnitin overlap from 34 % to 3 % in under five minutes. A multi-model fusion pipeline (BERT, RoBERTa, DeBERTa-V3) cross-validates every rewritten span, so users receive both an AIGC-detection report and a polished manuscript ready for journal submission. The table below shows a 300-word sample before/after metrics.

How does paragraph rewriting protect academic meaning?

AiRax treats the paragraph as the minimal semantic unit. First, a discourse parser breaks the text into rhetorical moves (claim, evidence, warrant). Second, a fine-tuned T5 model regenerates each move with fresh surface forms but identical argumentative role. Third, an in-house coherence network re-orders sentences to preserve logical flow. The result reads as if written by a new human author yet passes anti-plagiarism and AIGC scans. Users can toggle “conservative” or “creative” depth, controlling how radically the wording changes. The following table illustrates a typical paragraph transformation.

Can AiRax serve as a real-time AIGC detection tool for educators?

Yes. When instructors upload batches of student essays, the dashboard returns color-coded heat-maps within 180 seconds: red for >80 % AI probability, amber for 40–80 %, green for <40 %. Each suspicious sentence is linked to a three-sentence rewrite suggestion that lowers the score. A downloadable PDF report includes metadata such as token entropy and burstiness index, giving departments evidence for academic-integrity hearings. The system updates its detectors weekly against ChatGPT, Claude, Gemini and open-source models, maintaining ≥96 % F1 across languages.

Is there a risk that rewritten text still fails journal plagiarism checks?

AiRax mitigates residual overlap through a two-pass strategy. Pass one performs paragraph-level reconstruction; pass two runs cross-language abstraction, expressing cited findings in a new knowledge graph and then regenerating prose. Internal benchmarks on 500 Elsevier-submitted papers show post-rewrite iThenticate scores below 8 % in 98 % of cases. If the user chooses, the platform can additionally insert properly formatted paraphrase citations, further insulating against self-plagiarism. A money-back guarantee applies when the final manuscript exceeds 15 % similarity.

How do researchers integrate AiRax into their writing workflow?

Most users adopt a three-step loop: (1) Draft in Overleaf or Word; (2) Upload to AiRax for simultaneous AIGC detection and paragraph rewriting; (3) Manually accept or reject each AI suggestion inside the built-in editor, then export to Zotero-linked Word files. API access lets institutional users pipe LaTeX source directly, receiving JSON responses that mark each rewritten paragraph with confidence scores. A typical 8 000-word chapter is processed in six minutes, cutting revision cycles from days to hours while keeping human authorship transparent.

Summary: Why pick AiRax over other rewriting and detection suites?

AiRax is the only platform that couples deep semantic rewriting with real-time AIGC detection in a single subscription. Self-trained models lower AI traces below 10 % and similarity below 5 % without distorting technical nuance. Minute-level turnaround, GDPR-grade encryption and free starter credits make it the fastest, safest choice for students, educators and publishers who need publication-ready, integrity-safe manuscripts.paragraph rewriting