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Our patented AI checker is the most accurate detector on the market! Don't believe us? Try it for yourself!
Keyword density helper – This tool comes with a built-in keyword density helper in some ways similar to the likes of SurferSEO or MarketMuse the difference being, ours is free! This feature shows the user the frequency of single or two word keywords in a document, meaning you can easily compare an article you have written against a competitor to see the major differences in keyword densities. This is especially useful for SEO’s who are looking to optimize their blog content for search engines and improve the blog’s visibility.
You can also easily compare text by copying and pasting it into each field, as demonstrated below.
Ease of use
Our text compare tool is created with the user in mind, it is designed to be accessible to everyone. Our tool allows users to upload files or enter a URL to extract text, this along with the lightweight design ensures a seamless experience. The interface is simple and straightforward, making it easy for users to compare text and detect the diff.
Multiple text file format support
Our tool provides support for a variety of different text files and microsoft word formats including pdf file, .docx, .odt, .doc, and .txt, giving users the ability to compare text from different sources with ease. This makes it a great solution for students, bloggers, and publishers who are looking for file comparison in different formats.
Protects intellectual property
Our text comparison tool helps you protect your intellectual property and helps prevent plagiarism. This tool provides an accurate comparison of texts, making it easy to ensure that your work is original and not copied from other sources. Our tool is a valuable resource for anyone looking to maintain the originality of their content.
User Data Privacy
Our text compare tool is secure and protects user data privacy. No data is ever saved to the tool, the users’ text is only scanned and pasted into the tool’s text area. This makes certain that users can use our tool with confidence, knowing their data is safe and secure.
Compatibility
Our text comparison tool is designed to work seamlessly across all size devices, ensuring maximum compatibility no matter your screen size. Whether you are using a large desktop monitor, a small laptop, a tablet or a smartphone, this tool adjusts to your screen size. This means that users can compare texts and detect the diff anywhere without the need for specialized hardware or software. This level of accessibility makes it an ideal solution for students or bloggers who value the originality of their work and need to compare text online anywhere at any time.
As artificial intelligence becomes increasingly integrated into education, publishing, and digital communications, reliably detecting AI-generated content — especially in underrepresented languages like Arabic — has become crucial.
A major study, “The Arabic AI Fingerprint: Stylometric Analysis and Detection of Large Language Models Text,” rigorously tested the performance of state-of-the-art AI content detectors across a range of Arabic datasets.
Here’s how Originality.ai’s multilingual AI detector stacked up.
Learn more about AI detection and AI detection accuracy in our AI Detection Accuracy Review and a Meta-Analysis of Third-Party AI Detection Studies. Then, get further insight into our Multilingual AI Detector.
The study, conducted by researchers at King Fahd University of Petroleum and Minerals, set out to answer a pressing question: Can current AI detectors distinguish between human-written and AI-generated Arabic text?
It evaluated content from both academic and social media sources, generated by leading large language models (LLMs), using a suite of stylometric and machine learning methods.
The study and our benchmark used standard metrics for evaluating AI detection accuracy:
All metrics were calculated separately for each text source (Human, ALLaM, Jais, LLaMA, OpenAI).
In the research paper, the authors trained their detector as a multi-class classifier: for each input text, the model predicts whether it was written by a human or by one of the AI models (ALLaM, Jais, Llama, OpenAI).
This allows them to calculate per-class Precision, Recall, and F1-score for each label — including “Human” — since the classifier can make various types of mistakes (e.g., calling a human text “ALLaM” or “Jais”).
However, for fair comparison with Originality.ai (which only distinguishes “AI” vs “Human”), it makes sense to simplify the evaluation for human data:
Definition: FPR (False Positive Rate) – For the human dataset, if the model predicts any label other than “Human” for a sample, it is counted as a false positive.
Originality.ai achieved perfect (100%) or near-perfect accuracy and F1-score on all AI-generated academic abstract datasets, outperforming the research’s own fine-tuned detectors.
For OpenAI social posts, Originality.ai reached F1-scores over 99% — higher than the research baseline.
Across both academic and social datasets, Originality.ai kept the false positive rate extremely low (as low as 1.09% in academic abstracts and 4.37% in social media), ensuring human writing is rarely misclassified.
Originality.ai’s multilingual AI detection tool isn’t just a contender — it’s a leader in the detection of Arabic AI-generated text. Its results consistently match or exceed the best academic models, achieving industry-leading accuracy with minimal false positives.
For educators, publishers, and institutions looking to maintain integrity in detecting AI Arabic content, Originality.ai’s AI detector is the most accurate.
Further Reading:
No, that’s one of the benefits, only fill out the areas which you think will be relevant to the prompts you require.
When making the tool we had to make each prompt as general as possible to be able to include every kind of input. Not to worry though ChatGPT is smart and will still understand the prompt.
Originality.ai did a fantastic job on all three prompts, precisely detecting them as AI-written. Additionally, after I checked with actual human-written textual content, it did determine it as 100% human-generated, which is important.
Vahan Petrosyan
searchenginejournal.com
I use this tool most frequently to check for AI content personally. My most frequent use-case is checking content submitted by freelance writers we work with for AI and plagiarism.
Tom Demers
searchengineland.com
After extensive research and testing, we determined Originality.ai to be the most accurate technology.
Rock Content Team
rockcontent.com
Jon Gillham, Founder of Originality.ai came up with a tool to detect whether the content is written by humans or AI tools. It’s built on such technology that can specifically detect content by ChatGPT-3 — by giving you a spam score of 0-100, with an accuracy of 94%.
Felix Rose-Collins
ranktracker.com
ChatGPT lacks empathy and originality. It’s also recognized as AI-generated content most of the time by plagiarism and AI detectors like Originality.ai
Ashley Stahl
forbes.com
Originality.ai Do give them a shot!
Sri Krishna
venturebeat.com
For web publishers, Originality.ai will enable you to scan your content seamlessly, see who has checked it previously, and detect if an AI-powered tool was implored.
Industry Trends
analyticsinsight.net
Tools for conducting a plagiarism check between two documents online are important as it helps to ensure the originality and authenticity of written work. Plagiarism undermines the value of professional and educational institutions, as well as the integrity of the authors who write articles. By checking for plagiarism, you can ensure the work that you produce is original or properly attributed to the original author. This helps prevent the distribution of copied and misrepresented information.
Text comparison is the process of taking two or more pieces of text and comparing them to see if there are any similarities, differences and/or plagiarism. The objective of a text comparison is to see if one of the texts has been copied or paraphrased from another text. This text compare tool for plagiarism check between two documents has been built to help you streamline that process by finding the discrepancies with ease.
Text comparison tools work by analyzing and comparing the contents of two or more text documents to find similarities and differences between them. This is typically done by breaking the texts down into smaller units such as sentences or phrases, and then calculating a similarity score based on the number of identical or nearly identical units. The comparison may be based on the exact wording of the text, or it may take into account synonyms and other variations in language. The results of the comparison are usually presented in the form of a report or visual representation, highlighting the similarities and differences between the texts.
String comparison is a fundamental operation in text comparison tools that involves comparing two sequences of characters to determine if they are identical or not. This comparison can be done at the character level or at a higher level, such as the word or sentence level.
The most basic form of string comparison is the equality test, where the two strings are compared character by character and a Boolean result indicating whether they are equal or not is returned. More sophisticated string comparison algorithms use heuristics and statistical models to determine the similarity between two strings, even if they are not exactly the same. These algorithms often use techniques such as edit distance, which measures the minimum number of operations (such as insertions, deletions, and substitutions) required to transform one string into another.
Another common technique for string comparison is n-gram analysis, where the strings are divided into overlapping sequences of characters (n-grams) and the frequency of each n-gram is compared between the two strings. This allows for a more nuanced comparison that takes into account partial similarities, rather than just exact matches.
String comparison is a crucial component of text comparison tools, as it forms the basis for determining the similarities and differences between texts. The results of the string comparison can then be used to generate a report or visual representation of the similarities and differences between the texts.
Syntax highlighting is a feature of text editors and integrated development environments (IDEs) that helps to visually distinguish different elements of a code or markup language. It does this by coloring different elements of the code, such as keywords, variables, functions, and operators, based on a predefined set of rules.
The purpose of syntax highlighting is to make the code easier to read and understand, by drawing attention to the different elements and their structure. For example, keywords may be colored in a different hue to emphasize their importance, while comments or strings may be colored differently to distinguish them from the code itself. This helps to make the code more readable, reducing the cognitive load of the reader and making it easier to identify potential syntax errors.
With our tool it’s easy, just enter or upload some text, click on the button “Compare text” and the tool will automatically display the diff between the two texts.
Using text comparison tools is much easier, more efficient, and more reliable than proofreading a piece of text by hand. Eliminate the risk of human error by using a tool to detect and display the text difference within seconds.
We have support for the file extensions .pdf, .docx, .odt, .doc and .txt. You can also enter your text or copy and paste text to compare.
There is never any data saved by the tool, when you hit “Upload” we are just scanning the text and pasting it into our text area so with our text compare tool, no data ever enters our servers.
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This table below shows a heat map of features on other sites compared to ours as you can see we almost have greens across the board!
We believe that it is crucial for AI content detectors reported accuracy to be open, transparent, and accountable. The reality is, each person seeking AI-detection services deserves to know which detector is the most accurate for their specific use case.
