Your Learning System,
Powered by AI Grading
Next-Generation AI Writing Feedback
Academic Expertise Combined with Data-Driven Development
Our product is a result of extensive research and development by academic professionals and experts in the field of natural language processing and machine learning.
Our grading engine has been trained on hundreds of thousands of writing essays to ensure that it is reliable and produces accurate feedback on writing for English language learning students.
Boost your Learning System with a Simple API
1
Your users write their essay in your education system linked with Gradingly
2
Our AI powered grading engine receives and grades the essay via the API
3
Results are returned and writing grades with feedback shown in your system
1
Your users write their essay in your education system linked with Gradingly
2
Our AI powered grading engine receives and grades the essay via the API
3
Results are returned and writing grades with feedback shown in your system
Empower Your Business with AI and Gain a Competitive Edge
Utilising various AI techniques, our engine is trained on thousands of essays to provide accurate results
Trust in the speed and precision of our API. Receive a fully marked essay within 30 seconds.*
Gradingly is working with governments, businesses and education providers worldwide
Utilising various AI techniques, our engine is trained on thousands of essays to provide accurate results
Trust in the speed and precision of our API. Receive a fully marked essay within 30 seconds.*
Gradingly is working with governments, businesses and education providers worldwide
Optimised To Global Standards
Aligned to the CEFR (Common European Framework of Reference)
The CEFR is a global benchmark for language proficiency that provides learners and educators with a standardised approach to language learning.
At our product, we recognise the importance of the CEFR for English language learning and have designed our writing feedback engine to align with these standards.
Optimised To Global Standards
Aligned to the CEFR (Common European Framework of Reference)
The CEFR is a global benchmark for language proficiency that provides learners and educators with a standardised approach to language learning.
At our product, we recognise the importance of the CEFR for English language learning and have designed our writing feedback engine to align with these standards.
Unlock Actionable Insights: Explore Available Metrics
About
The overall writing score encompasses several metrics and is designed to provide an overall evaluation of the given text. The score primarily takes into account the text's error rate, achieved CEFR level, topic alignment, and tone.
As an integral component of the API, you have the option to customise this score to ensure that it aligns with your academic objectives.
Sample output:
About
This important metric shows an estimation of the CEFR (Common European Framework of Reference) level attained based on the submitted text.
Trained on hundred of thousands of essays, our advanced CEFR Level Detection algorithm filters out non-essential words, including commonly used word fillers such as 'the', 'a', 'it', among others, to produce an accurate prediction of the achieved level.
Sample output:
About
This metric estimates the degree to which an essay conforms to the topic requirements can provide crucial insights into the essay's effectiveness.
By analysing the essay's content, this indicator can accurately predict how closely the essay is aligned with the assigned topic. This is particularly useful in identifying areas of improvement, such as adding or removing content, in order to better address the writing task's requirements.
Sample output:
About
Our tone estimation metric provides a valuable tool for users and administrators in determining the degree to which the writing requirements have been followed. Understanding the tone of a text is crucial in accurately assessing its appropriateness for a specific audience or purpose.
This estimation metric can predict whether the writing style is formal or informal based on the text's intended target.
Sample output:
About
Measuring and understanding the number of errors and warnings in a text can provide valuable insights into the overall performance of a written work.
This metric uses a specialised algorithm to identify and quantify the errors and warnings present in the text, including issues such as spelling mistakes, punctuation errors, and grammatical inconsistencies.
Sample output:
About
Understanding the number of letters per word and sentence is a crucial factor in accurately determining the level of complexity used in an essay.
By analysing the length of words and sentences, this metric can provide a reliable estimation of the text's readability, which is a critical factor in determining its effectiveness in conveying information to the reader.
Sample output:
About
This metrics shows the proportion of unique words compared to the proportion of stop words and repetitions in an essay can provide valuable insights into the overall quality of the written work.
This metric uses advanced algorithms to analyse the essay's content and provide accurate estimations of the proportion of unique words, stop words, and repetitions present in the text.
Sample output:
About
This metric uses GPT-3 to analyse the written work and provide feedback in the form of three key bullet points, highlighting areas of improvement and suggesting specific recommendations to help users improve their writing abilities.
Sample output:
About
Rewriting a text with faults can be a highly beneficial exercise for improving writing skills. By identifying and correcting errors in grammar, syntax, and structure, writers can strengthen their understanding of the rules of the language and refine their writing style.
Sample output:
“I currently reside in Athens, a city that's always bustling and picturesque, particularly in August. As most people travel elsewhere for their holidays during that month, Athens becomes less crowded, allowing you to visit its various shops and restaurants with your local friends at your leisure. You can also catch a movie or attend concerts by well-known singers.If you're into sports, you'll find plenty of facilities in Athens that cater to your interests.
Personally, I love being in Athens in August because I'm a skilled football player, and my favorite football pitch is conveniently located near my uncle's house. I frequently visit this pitch with my cousins, Mary and Nick, not only to play football but also to grab a meal at the owner's restaurant. If you're an enthusiastic and happy individual looking to make the most of your summer, don't hesitate to visit Athens - it's the perfect destination for you.”
About
Our error analysis table provides a comprehensive overview of the errors present in a written work, allowing users to quickly and easily identify issues that may be impacting the text's overall quality and effectiveness. This table uses a specialised algorithm to analyse the text and categorise errors based on type, frequency, and severity, providing a detailed breakdown of the issues present in the text.
Sample output:
About
The indicator that displays the aggregate number of spelling mistakes in a written work is a crucial tool for ensuring the overall quality and accuracy of the text.
This indicator uses an algorithm to analyse the text and identify words that are spelled incorrectly, providing a reliable estimation of the number of spelling mistakes present in the text.
Sample output:
About
Readability is about clarity. The better the writing, the clearer your message is to the reader. Clear and concise writing ensures that the intended message is conveyed in a manner that is easily understood by the reader
This metric provides a combined readability score, derived from sources such as the Flesch-Kincaid score and the Dale-Chall score, to determine how easily readers can comprehend the essay.
Sample output:
-
Unique Words
About
This metrics shows the proportion of unique words compared to the proportion of stop words and repetitions in an essay can provide valuable insights into the overall quality of the written work.
This metric uses advanced algorithms to analyse the essay's content and provide accurate estimations of the proportion of unique words, stop words, and repetitions present in the text.
Sample output:
-
Written AI Feedback
About
This metric uses GPT-3 to analyse the written work and provide feedback in the form of three key bullet points, highlighting areas of improvement and suggesting specific recommendations to help users improve their writing abilities.
Sample output:
-
Error Analysis
About
Our error analysis table provides a comprehensive overview of the errors present in a written work, allowing users to quickly and easily identify issues that may be impacting the text's overall quality and effectiveness. This table uses a specialised algorithm to analyse the text and categorise errors based on type, frequency, and severity, providing a detailed breakdown of the issues present in the text.
Sample output:
