Última atualização: 28 de junho de 2026
[IMPORTANT: This methodology is still being updated and may not yet contain fully accurate information.]
Current production model: GoHumanize Model v1.0
Released: June 2026
Architecture: One multilingual 4-billion-parameter open-weight language model, fully fine-tuned for AI text humanization
GoHumanize is an AI writing tool designed to transform stiff, repetitive, generic, or overly mechanical text into clearer and more natural writing.
Its purpose is not simply to replace individual words. GoHumanize considers how sentence structure, vocabulary, rhythm, transitions, tone, emphasis, and paragraph flow work together across an entire passage.
This page explains how GoHumanize is developed, how submitted text is transformed, how external testing is conducted, and what limitations users should understand.
AI writing systems can produce grammatically correct and informative text, but their output may contain recurring patterns that make it feel predictable or artificial.
These patterns may include:
GoHumanize was created to improve these characteristics without forcing every passage into the same voice or writing style.
The goal is to make writing clearer, more varied, and more appropriate for its context while preserving the author’s underlying message.
GoHumanize develops and improves its models through dataset preparation, full model fine-tuning, evaluation, and continued refinement.
The model is trained to recognize general linguistic patterns involving sentence structure, vocabulary, rhythm, tone, transitions, paragraph organization, and writing variation.
It is designed to transform user-submitted text by applying these learned patterns. It is not designed to retrieve and reproduce specific source documents.
Based on publicly available text and AI-generated text used as source material, we created and curated approximately 200,000 paired examples consisting of AI-style text and natural human-written text.
Before selecting the final dataset, we generated and evaluated several million candidate pairs.
Candidate pairs were cleaned, deduplicated, filtered, and reviewed to remove:
All dataset figures are approximate and may change as examples are reviewed, corrected, removed, or replaced.
The training dataset covers seven supported language variants:
Development and quality review have focused primarily on English, which is GoHumanize’s primary language.
Other supported languages are included in training and evaluation, but performance may vary depending on the language, content type, and submitted text.
Training examples cover seven main categories:
The dataset also includes different tones, sentence lengths, vocabulary levels, paragraph structures, and degrees of formality.
This variety helps prevent the model from applying the same voice, structure, or formula to every passage.
GoHumanize uses a multilingual open-weight language model that has been fully fine-tuned specifically for AI text humanization.
Full fine-tuning updates the model’s parameters for the transformation task rather than adding only a small adapter layer.
During training, the model learns patterns related to:
GoHumanize currently uses one multilingual model across all supported languages.
Before the first production release, several beta models were trained using smaller datasets.
These versions were used to refine:
Lessons from these beta versions were incorporated into the production model.
GoHumanize uses a multi-stage process rather than relying on simple synonym replacement or one generic rewriting instruction.
The user submits the text they want to improve and may select:
These settings guide the style and extent of the transformation.
GoHumanize considers the passage as a whole, including:
The system identifies areas that may sound rigid, repetitive, generic, overly formal, or mechanical.
No individual word, punctuation mark, or sentence pattern is treated as proof that text was generated by AI. Multiple writing characteristics are considered together to determine where the passage may benefit from improvement.
The submitted text is processed by GoHumanize’s fine-tuned model.
Depending on the content and selected settings, the model may:
GoHumanize focuses on structural rewriting rather than isolated word substitution.
A passage can use different vocabulary while retaining the same predictable structure, rhythm, and tone. For this reason, replacing a few words is often not enough to make writing feel more natural.
Before the result is returned, the transformed text is checked for basic processing issues, including:
Additional adjustments may be applied where appropriate.
The revised text is returned to the user for review.
Automated transformations are not always perfect. Users should verify important facts, names, figures, quotations, instructions, specialized terminology, and intended meaning before publishing, submitting, or relying on the result.
The examples below demonstrate some of the writing characteristics GoHumanize is designed to improve. Actual results depend on the submitted text and selected settings.
Before:
The system analyzes the text. It identifies writing patterns. It generates a revised version. The result is more natural.
After:
The system first analyzes how the text is written. Once it identifies repetitive or mechanical patterns, it revises the passage to improve its flow and make it feel more natural.
Before:
Furthermore, the tool improves readability. Moreover, it adjusts sentence structure. Additionally, it reduces repetition.
After:
The tool improves readability by adjusting sentence structure and reducing unnecessary repetition.
Before:
It is essential to utilize an effective methodology in order to facilitate improved outcomes.
After:
Using a clear method can lead to better results.
Before:
The tool makes the text more natural. It improves naturalness by making the writing sound less artificial. This results in more natural writing.
After:
The tool reduces artificial-sounding patterns so the text reads more naturally.
GoHumanize uses independent third-party tools for publicly reported detector testing.
The external evaluation uses:
These tools are used to evaluate GoHumanize output.
Each production model is evaluated using 100 held-out samples that are separate from its training data.
The test set:
Because the detectors use different scoring systems and labels, each result is reported using the terminology provided by the applicable tool.
[Results will be added after full testing is complete.]
Published results will identify:
External detector results reflect the tools, detector versions, and test conditions available on the stated test date. They are not guarantees of future or individual results.
GoHumanize is designed to improve naturalness and reduce repetitive or artificial-sounding writing patterns. It does not guarantee that any third-party detector will classify a particular text as human-written.
AI detectors use different:
Their results may also change when a detector is updated.
Results can vary depending on:
A detector score should not be treated as definitive proof of authorship.
Text submitted to GoHumanize is transmitted using encrypted connections and processed by GoHumanize’s fine-tuned model.
GoHumanize does not use text submitted by users through the service to train its models.
For registered users, humanization history is stored in their accounts so previous results can be accessed from the dashboard. Users can delete their entire history at any time.
GoHumanize does not sell user content.
Further information about data processing, retention, account history, deletion, and user rights is available in our Privacy Policy.
Like any AI-powered writing tool, GoHumanize may occasionally produce text that is:
Results may vary depending on the quality, language, length, format, subject, and writing style of the submitted text.
GoHumanize should be treated as a writing assistant rather than a substitute for human review, factual verification, or professional judgment.
Users are responsible for reviewing the output and using GoHumanize in accordance with applicable rules and disclosure requirements. For more information, please review our Ethics Statement and Acceptable Use Policy.
AI-generated writing continues to evolve. New language models produce different vocabulary, sentence structures, and stylistic patterns. Users also apply writing tools to new languages, formats, and use cases.
GoHumanize may therefore be updated to improve:
Updates may be triggered by:
Material changes are documented in the version history below.
Version History
Several beta models were trained using smaller datasets before the first production release.
The beta development process focused on:
The first production version of the GoHumanize humanization model.
This methodology will be reviewed whenever GoHumanize materially changes:
The “Last updated” date at the top of this page will be revised when a material methodology change is published.