7 Free AI Tools for Text Proofreading | Easy-to-Understand Comparison of Each Tool's Features

Proofreading AI is a general term for systems that use AI (artificial intelligence) natural language processing technology to automatically detect errors and areas for improvement in text and suggest corrections. Recently, with the advancement of large language models (LLMs), proofreading has evolved beyond mechanically matching words or strings to include corrections based on the meaning of the text. First, let's look at the basic mechanism and how it differs from previous proofreading methods.

1-1. What Text Proofreading AI Can Do

Text proofreading AI not only detects typographical errors and grammatical mistakes but also automatically handles tasks such as pointing out inconsistencies in notation and rephrasing difficult expressions into clearer ones. What sets it apart from conventional tools that mechanically judge based on dictionaries and rules is its ability to make decisions considering the surrounding context.

For example, it can detect mix-ups of homophones like "bridge" and "chopsticks," as well as conversion errors such as "probability" and "establishment." Even for documents spanning hundreds of pages, it can quickly check whether the notation is consistent throughout.

1-2. Differences Between Typo and Omission Checks, Consistency Confirmation, and Paraphrasing Support

Even though they are all called "proofreading," the tasks differ depending on the purpose. "Typo and omission checks" involve finding obvious errors, "consistency confirmation" involves standardizing variations such as "user/user" or "can/can" (different spellings), and "paraphrasing support" involves rephrasing convoluted expressions to make them easier to understand.

Since the purpose differs, the tools that excel also change, so it is important to clearly define "what you want to proofread" before choosing.

1-3. Differences from Human Proofreading and Reviewing

The strength of human proofreading lies in the ability to grasp the document's purpose, the reader, and the writer's intent, allowing for adjustments to subtle nuances. However, proofreading that relies on the experience and intuition of veteran staff tends to be subjective. If standards are not documented, the accuracy of checks varies depending on the person in charge, resulting in inconsistent document quality.

On the other hand, AI can check quickly and according to consistent standards, but it struggles with final judgments such as fact-checking and whether the style and tone fit the company's unique voice. It is not practical to rely solely on either one; rather, it is realistic to leverage each one's strengths and divide the roles accordingly.

The appeal of free AI text proofreading lies in its ability to streamline proofreading tasks without any initial cost. It is useful when considering the introduction of paid tools or business-oriented services. Here, we will organize the main benefits of using free tools.

2-1. Streamlining the Process of Checking Typographical Errors and Omissions

Proofreading work that used to involve visually checking each character one by one can now be completed in just a few minutes using AI. In fact, there are cases where proofreading a press release, which previously took three hours, can now be done in about 30 minutes. Detecting simple typographical errors and omissions is where AI excels the most, and it can even identify subtle inconsistencies in notation that humans tend to overlook.

2-2. Easier to Improve Readability of Text

Text proofreading AI can point out causes of "difficulty in reading," such as sentence length, convoluted expressions, and mismatches between subject and predicate, and suggest rephrasing for clearer communication. Its strength lies not only in correcting mistakes but also in enhancing the overall readability of the text. Even those who are not accustomed to writing can maintain a certain level of readability by referring to the AI's suggestions.

2-3. Usable for a wide range of documents such as emails, materials, and articles

From business emails to proposals, internal reports, and web content, free AI’s strength lies in its ability to be used regardless of the type of text. No special settings are required; you can simply paste the text to check various documents. It can be easily utilized in all kinds of daily document creation situations.

2-4. You can check the usability before introducing paid tools

By using free tools or free plans, you can verify the accuracy, usability, and compatibility of AI proofreading with your company's documents without incurring any costs. By actually trying it out with your own documents, you can concretely grasp "how much can be automated" and "what kinds of documents it is suitable for." It is very useful as a low-risk way to test before introducing full-fledged paid tools or business-oriented services.

Free AI for text proofreading is easy to use, but there are also constraints and risks unique to business documents. Before deciding that "proofreading with free AI is sufficient," please pay attention to the following points.

3-1. Free plans have limits on character count and features

Many free tools set limits on the number of characters that can be input at one time and the number of uses per day. They are often restricted to around 500 to 2,000 characters, which can become a bottleneck when processing long manuals or large volumes of documents in actual business operations.

3-2. There are cases where specialized terms and in-house terminology cannot be correctly recognized

General-purpose AI judges based on standard Japanese, so it may mistakenly treat industry-specific technical terms or expressions used only within the company as errors and correct them. Unique notations that have been used internally for a long time may be corrected as mistakes, or conversely, expressions that should be standardized may be overlooked. In highly specialized fields such as manufacturing, medical care, and legal affairs, whether terms and notations can be registered in a dictionary or customized independently greatly affects practical usability.

3-3. Without proofreading standards, correction policies become inconsistent

If there is no internal standard for "what is considered correct" in the first place, the AI can only judge based on general Japanese language rules. As a result, the way instructions are given and the correction proposals adopted vary by person in charge, causing inconsistencies in proofreading results even for the same document. Leaving the AI to handle things without clearly defining standards such as punctuation usage or the distinction between kanji and hiragana can actually lead to unstable quality.

3-4. Caution is Required When Inputting Confidential Information and Internal Documents

Free generative AI tools may use the input data for AI retraining depending on the settings, and there is a possibility that the data may be stored and reused. Inputting documents containing unpublished technical information or customer data as-is poses a risk of information leakage. When handling business documents, it is essential to choose an environment for corporations that guarantees the input data will not be used for training, or a system that allows API connections so you can use it without worrying about data being disclosed or shared.

3-5. The final decision must be made by a human

AI suggestions may include factual errors (hallucinations) or corrections that do not fit the context. Especially for numbers, proper nouns, and specialized content, blindly trusting AI output can actually degrade quality. It is important to position AI as a tool that assists verification and proposal, and to adopt the “human-in-the-loop” approach where the final decision on whether to accept corrections is made by a person.

From here, we will introduce seven representative AI tools that can be used for free proofreading.

4-1. ChatGPT

ChatGPT is a conversational AI developed by OpenAI and is widely recognized as a leading example of generative AI. If you specify the purpose clearly, such as "polish it carefully as a business document" or "focus on readability," it will flexibly revise according to your intent. Although the free version has limits on usage frequency and character count and requires caution in handling input content, by crafting prompts well, it can handle a wide range of tasks from checking typos to adjusting tone and summarizing. If you want to start experiencing AI proofreading, it is a strong candidate.

4-2. Gemini

Gemini is a generative AI provided by Google, with its greatest appeal being seamless integration with Google Workspace. For organizations using Google Workspace, you can create documents in Google Docs, Sheets, and Slides while completing proofreading on the spot. Another strength is its ability to reflect the latest information based on Google's vast data.

4-3. Microsoft Copilot

An AI built into Microsoft 365 by default, allowing you to proofread and rewrite text while keeping Word or Outlook open. Organizations using Microsoft 365 don’t need to switch to another tool. It comes standard with commercial data protection that ensures input data is not used for model training, so you can confidently entrust documents containing confidential information.

4-4. Google Docs Proofreading Feature

Google Docs comes with a built-in proofreading feature that marks spelling mistakes with a red underline and grammatical errors with a blue underline. You can simply click on the highlighted sections to accept or ignore the corrections, and it also offers a "Suggestion Mode" which is useful when editing with multiple people. However, since the Japanese grammar check is not yet fully reliable, it is recommended to use it as a basic verification tool and combine it with other tools.

4-5. Word's "Editor" Feature

This is a proofreading feature built into Microsoft Word that allows you to check for typos and grammatical errors while writing. Since it is integrated into your usual writing environment, there is no need to copy and paste into another tool, and no additional cost is required. Although its advanced contextual proofreading does not match that of dedicated AI, it is considered sufficient as a proofreading function for everyday document creation.

4-6. Shodo

Shodo is a tool that uses context-aware AI proofreading to detect errors in particles, unnatural Japanese expressions, typos, and more. It also supports consistency checks such as discrepancies between dates and days of the week. Full-scale proofreading that verifies the accuracy of content based on background information is available in the higher-tier plans. Features like browser extensions for Chrome and Edge, integration with Word and Google Docs, functions to unify variations in notation, and settings for writing rules are included in the paid plans. The free plan mainly offers web-based proofreading with limitations on the number of characters and usage frequency.

4-7. PRUV

PRUV is a text proofreading tool that can be used in a browser. It is convenient for quickly reviewing short texts since you can try basic typo and spelling checks without registering as a member. To use features like inconsistency checks and user dictionaries, free membership registration is required, and proofreading using generative AI is available in the paid Pro plan. The free usage mainly focuses on rule-based checks, and there is a limit on the number of characters you can input.

While free tools are convenient, when it comes to business documents, issues such as unifying proofreading standards, security, and compatibility with existing workflows come into question. Here, we introduce AI and document support tools designed with business use in mind.

5-1. MTrans for Office

MTrans for Office is an add-in type AI proofreading, writing, and translation tool for Microsoft Office developed by Human Science Co., Ltd. It goes beyond checking formal aspects such as typos and inconsistencies in notation, allowing AI to verify quality perspectives that have traditionally been handled by humans, including technical communication viewpoints and compliance with standards and style guides. Proofreading rules support both natural language instructions (prompts) and search-and-replace using regular expressions, enabling the use of both rule-based and generative AI-based approaches. Multiple rules can be grouped, allowing rule sets to be switched according to the document’s purpose. Rules can be centrally managed and shared online, enabling multiple users to proofread based on the same standards. Input data is not reused for AI training, so confidential documents can be handled with confidence.

5-2. Benefits of Utilizing AI in Office Documents

You can complete everything from proofreading to corrections with a single click while keeping familiar Word, Excel, or PowerPoint open. Since there is no need to copy and paste text into another tool or convert file formats, AI proofreading can be introduced without changing your daily workflow. No matter how advanced an AI proofreading tool is, it will not be fully utilized unless it becomes part of daily work. Therefore, whether it can be seamlessly integrated into the familiar environment is a crucial factor that affects its adoption after implementation. Additionally, because proofreading can be done while preserving the document’s structure and formatting such as tables, figures, and bullet points, there is no need to spend time readjusting the layout after corrections.

5-3. Features of Tools That Support Translation, Summarization, Rewriting, and Proofreading All Together

MTrans for Office is characterized by its ability to handle not only proofreading but also translation, summarization, and rewriting within a single environment. With MTrans for Office, you can choose from multiple translation engines such as OpenAI, Google, Microsoft, and DeepL, and compare the translation results. After proofreading the original text to improve its quality, you can proceed to translation in the same environment, reducing the hassle of exchanging data between tools and minimizing security risks, thereby enhancing the quality of both the original and translated texts together.

5-4. Differentiating Between Free Tools and Business-Oriented Tools

The basic principle for differentiation is to choose based on your purpose. If you want to easily try it out individually, free tools are suitable; if you want to standardize quality as an organization and handle confidential documents securely, business-oriented tools are more appropriate. Free tools are suitable for verification and individual checks, while business-oriented tools have strengths in accumulating proofreading standards as assets, ensuring security, and unifying quality across the entire team. Identifying your company's challenges—whether you want to reduce individual effort or standardize quality across the organization—is the shortcut to making the optimal choice.

When choosing an AI proofreading tool from the many available, it is important to assess not only the number of features and price but also how well it fits your company's actual business operations. Here, we organize the perspectives you should check when making comparisons.

6-1. Accuracy of Japanese Proofreading

Tools developed overseas may have limited support for Japanese and might overlook errors such as homophones or particle mistakes. It is important not to judge solely based on the features listed in the catalog but to actually test the tool with your company’s documents to verify its accuracy. Especially if you mainly handle Japanese business documents, prioritize confirming the quality of Japanese proofreading before deciding whether to implement the tool.

6-2. Scope of Support for Typographical Errors, Inconsistent Notation, and Style Adjustments

Depending on the tool, some only check for formal typographical errors, while others also support style adjustments and suggestions for improving sentence structure. The required scope of support varies greatly depending on whether your company’s priority is "reliably catching simple mistakes" or "enhancing the overall quality of the text." Be sure to thoroughly verify in advance that the tool’s scope of support matches your company’s needs.

6-3. Support for Technical Terms and Industry-Specific Terminology

Fields such as manufacturing, IT, healthcare, finance, and legal each have their own unique technical terms and expressions. Check whether the tool can correctly handle terms not found in general dictionaries, whether it allows you to register and manage glossaries, and whether it can perform checks based on industry standards such as IEC 82079-1 or the TC Association Japanese Style Guide. Since general-purpose AI may incorrectly correct technical terms, the extent to which customization is possible greatly affects its practical usability.

6-4. Security and Handling of Input Data

When corporations handle business documents, it is crucial to confirm that the input data will not be reused for training purposes and that secure data communication via API connections is ensured. Additionally, it is important to check whether access management features such as SSO (Single Sign-On) and IP address restrictions are available. Be sure to verify before implementation that there are no conflicts with your company’s security policies.

6-5. Compatibility with Office Documents and Existing Workflows

No matter how advanced a tool is, if it is difficult to integrate into the existing workflow, it will not take root on the ground. If there is the hassle of copying and pasting documents or uploading them to another platform, usage will gradually decline, and ultimately, the original manual process will be resumed. Whether proofreading and corrections can be completed within commonly used applications like Word, Excel, and PowerPoint is an important factor that determines whether the tool will be smoothly adopted after implementation.

6-6. Differences Between Free and Paid Plans

There are differences between free and paid plans in terms of character limits, available features, and security measures. The free version is convenient, but when used for business purposes, limitations on functionality and data handling can become obstacles. It is important to compare the scope of what can be used for free with the value gained by opting for a paid plan (such as secure data transmission, unlimited usage, rule management features) and choose based on cost-effectiveness.

It is not uncommon for AI proofreading tools to fail to deliver the expected results. In many cases, the cause is not a lack of functionality in the tool itself, but rather improper usage or insufficient preparation before implementation. Here, we organize the common factors behind such failures.

7-1. Reflecting AI Suggestions Exactly as They Are

The correction proposals presented by AI are merely "suggestions." Accepting all of them as is does not necessarily improve quality and may even introduce corrections that do not fit the context. Proofreading business documents requires judgment that takes into account the document’s purpose, audience, and brand guidelines. Skipping the process where humans appropriately evaluate and selectively apply AI suggestions can cause the AI implementation to have a negative effect.

7-2. Proofreading and notation rules are not established

When the standards for proofreading are not clearly defined in words, it becomes ambiguous what the AI should judge as correct. As a result, there may be too many corrections pointed out, or important issues might be overlooked, causing a gap between the expected quality and the actual output. To prevent situations where long-used in-house notations are incorrectly corrected as errors, it is important to identify and organize proofreading rules before introducing the tool.

7-3. Making corrections that do not match the document’s purpose or audience

Even with the same content, appropriate expressions vary between materials intended for external audiences and internal memos, as well as between experts and general readers. If AI corrections are applied uniformly without considering the reader or the document’s purpose, the result can be a text that is harder to understand. For example, patient-facing documents in the medical field require replacing technical terms with simpler language. In this way, proofreading that consciously considers "who is being told what" for each document is essential.

7-4. Overlooking corrections that change the meaning in highly specialized documents

In technical documents and specifications, even slight rephrasing can change the meaning itself. Corrections suggested by AI that prioritize "readability" may become inaccurate from a specialist's perspective. For manuals and other documents with complex notation rules, it is essential to have a process where a person with expert knowledge verifies the accuracy of the meaning.

7-5. Lack of unified quality standards when used by multiple people

When using general-purpose generative AI for proofreading, if the way instructions are given and the points checked differ among individuals, the proofreading results can vary even for the same document. If only some members use AI in their own way, the efficiency gains remain limited to those individuals, and the overall return on investment for the organization stays low. It is essential to standardize proofreading rules and instruction methods across the organization and establish a system for sharing them to stabilize quality.

To ensure AI proofreading does not end as a temporary efficiency boost but becomes a continuous organizational strength, a phased introduction and operational design are essential. Here, we introduce the approach to successfully leveraging AI proofreading.

8-1. First, decide the target documents and scope of use

First, clarify which documents, who will use AI proofreading, and at what timing. Instead of expanding it company-wide all at once, it is more practical to start with documents or departments where effectiveness is expected. Narrowing down the target and scope makes it easier to measure the effect and facilitates spreading successful cases to other departments within the company.

8-2. Establish notation rules and terminology rules

The quality of AI proofreading is directly linked to the quality of the proofreading rules input. Summarize standards such as "polite form or plain form," "numbers in kanji or Arabic numerals," and "notation rules for industry-specific technical terms" into a document, and systematize them as a glossary or style guide that AI can reference. Once this foundation is in place, not only will the AI's proofreading accuracy stabilize, but it will also serve as a guideline for humans when performing tasks.

8-3. Separate the tasks assigned to AI from those checked by humans

Tasks that AI excels at, such as checking for typos, inconsistencies in notation, and routine rule verification, should be entrusted to AI. Meanwhile, humans should handle judgments about contextual appropriateness, evaluations of readability from the reader’s perspective, and confirmation of brand consistency. By clearly dividing these roles rather than leaving everything to AI, you can achieve both efficiency and quality. As AI evolves, the scope of tasks it can handle will expand, so it is advisable to periodically review and adjust the division of responsibilities.

8-4. Review proofreading results and improve the rules

While operating AI proofreading, review the trends of corrections and oversights, and update the proofreading rules. It is important not to try to create perfect rules from the start of the operation, but to gradually improve them based on actual proofreading results. Through this repetition, the accuracy of AI proofreading steadily improves over time.

8-5. Document operational rules when used by a team

When multiple people use AI proofreading, share the instructions, definitions of proofreading, and verification procedures in written form. Leaving the usage to individual discretion causes quality to vary by person and valuable know-how to be lost within the organization. By documenting operational rules and ensuring everyone follows the same procedures, consistent quality can be maintained even with personnel changes or organizational restructuring.

To truly achieve results with business documents, it is essential not to rely solely on tools but to consider them in combination with "document quality design." Here, we organize the foundational concepts behind this approach.

9-1. AI proofreading accuracy depends on the input documents and rule design

Many cases where people feel "AI accuracy is low" or "it doesn't fit the business" are actually not problems with the tool itself, but rather due to insufficient quality of the input documents or inadequate design of the proofreading rules. Without clear proofreading standards, no matter how advanced the AI is, the output quality will not be stable. To truly harness the effectiveness of AI proofreading, it is important to work on designing quality standards alongside or even before introducing the tool.

9-2. It is necessary to also verify the accuracy of meaning in technical documents and manuals

In technical documents and manuals, not only grammatical correctness but also the meaning of the descriptions and logical consistency greatly affect quality. While AI can produce grammatically correct and smooth sentences, it cannot guarantee the accuracy of specialized content. Meaning checks must be carried out by experts with specialized knowledge, and only by combining this with AI’s formal checks can reliable quality be ensured.

9-3. Standardizing Notation, Terminology, and Document Structure Leads to Stable Quality

Aligning notation and terminology and organizing the document structure form the foundation for stabilizing the effectiveness of AI proofreading. If proofreading rules can be centrally managed and shared online rather than individually, proofreading can be done according to the same standards even when personnel change, and revisions or additions to the rules are immediately reflected for everyone. Such a system prevents reliance on individuals and is the key to achieving stable document quality as an organization.

9-4. Consider Consulting Specialized Companies When Necessary

If you find it difficult to design proofreading rules or establish their operation, consulting specialized companies is also an effective option. Companies with long-standing expertise in technical communication, manual creation, and knowledge organization support everything from designing document quality standards tailored to each company, to building AI proofreading workflows and establishing their operation, working alongside you. By leveraging expert knowledge instead of struggling with tool implementation alone, you can reach results without detours.

Human Science provides comprehensive support from the design to the implementation and establishment of AI utilization.

＞ Click here for details on AI Proofreading Consulting (MTrans for Office)

Free AI proofreading tools are easy and convenient to use, but for business purposes, it is essential to differentiate usage according to the purpose and consider quality design. Finally, we will review the key points of this article once again.

10-1. Free AI Proofreading Tools Are Easy to Try but Require Appropriate Use According to Purpose

Free tools like ChatGPT, Gemini, and Shodo are attractive because they allow you to easily try AI proofreading without any cost. On the other hand, they have limitations such as character count restrictions and security constraints, so caution is needed when handling business documents. It is wise to first check usability with free tools, then use free tools for personal use and testing, and business-oriented tools for full-scale organizational use, depending on the purpose.

10-2. Confirm Security, Proofreading Standards, and Terminology Support for Business Use

When corporations use it for business documents, it is important that the input data is not used for learning and that it can accommodate the company’s proofreading standards and specialized terminology. Whether it provides a secure environment via API connection, has access controls such as SSO and IP restrictions, and can perform checks according to standards are also crucial points. Confirming these before implementation can help mitigate risks such as information leaks and quality inconsistencies.

10-3. To Make the Most of AI Proofreading, It Is Important to Improve Document Quality and Operational Rules

The effectiveness of AI proofreading is determined not only by "tool selection" but also by the "design of standards and rules." Business-oriented tools like MTrans for Office, which allow proofreading and corrections to be completed within Word, Excel, and PowerPoint, and enable proofreading rules to be shared and institutionalized within an organization, are a strong option for companies that want to build quality as an organizational asset. Rather than treating tool implementation as the goal, taking a comprehensive approach that includes establishing your own rules, style guides, and operational workflows is the key to continuously achieving results with AI proofreading.

Human Science provides comprehensive support from the design to the implementation and establishment of AI utilization.

＞ Click here for details on AI Proofreading Consulting (MTrans for Office)