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“Your writing assistant”

LanguageTool is primarily an AI editing tool: it improves existing texts with suggestions for grammar, spelling, punctuation, style, tone, and in some cases rephrasing, rather than primarily generating new content like a classic GenAI writer. It is available via web editor, browser, Word, Google Docs, LibreOffice, mail integrations, as well as on Windows/macOS/iOS, and supports more than 30 languages. For developers, there is also an HTTP API and an open-source core technology for self-hosting.
Language Tool

More than a Grammar Checker - Your writing assistant

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8.3/10 KIFOX Score – Very good

Location: Germany LanguageTooler GmbH, Boschstraße 23a, 22761 Hamburg, Germany. For the service/data protection context relevant today, Learneo officially states: Learneo, Inc., 2261 Market Street #10569, San Francisco, CA 94114, United States of America

Paraphrase Spell check Text generation
Free Free basic version for spelling, grammar, and style checking; some free services are also accessible without an account. Subscription Premium / Individual Advanced checks, longer texts, style and tone suggestions, as well as additional writing features compared to Free.

Teams All Premium features plus user management, Team Style Guide, Team Dictionary, and higher text lengths for teams.
Other Business DPA available; core functionality open source, own server possible locally or in the cloud; public HTTP API or developer options available.

Target audience
LanguageTool is aimed at people and teams who want to improve existing texts: private users, freelancers, marketing/communications teams, support teams, editorial teams, HR, sales, agencies, and companies with a high volume of written output. LanguageTool is also of interest to developers because the correction logic can be integrated via API or operated independently through the open-source core.

Outstanding features
Particularly strong are the context-aware correction of grammar, spelling, punctuation, style, and tone, multilingual use in 30+ languages, paraphrasing, personal and team style guides, Team Dictionary, the focused editor, as well as broad availability in browsers, Word, Google Docs, LibreOffice, and mail clients. For technical teams, HTTP API, self-hosting, and on-premise are added benefits.

Target audienceAssessment
Private individualsVery suitable – for spelling, grammar, punctuation, and style in many languages.
Self-employed / freelancersVery suitable – for emails, blog posts, proposals, website copy, and multilingual communication.
SMEs / teamsSuitable to very suitable – teams receive Premium features, Style Guide, Team Dictionary, and user management.
Developers / privacy-conscious teamsSuitable – the core function is open source and can be operated independently locally or in the cloud.
Large enterprisesConditionally suitable to suitable – Business/DPA available; for Premium on-prem or enterprise features, the specific contractual terms must be reviewed.

Hosting & Data

✅ = well covered ⚠️ = partial / indirect ❓ = not available / unclear
?

1) On-prem / local hosting
Meaning: The company operates the solution on its own hardware or within its own infrastructure. In the strictest sense, not only the application runs locally, but ideally the model as well.

2) Private cloud / data center
Meaning: The solution runs in a dedicated or more clearly separated cloud environment, often with a hosting provider or hyperscaler, but in a German data center or in a particularly controlled environment.

3) EU SaaS / managed
Meaning: The provider operates the solution itself as a service. The company uses the tool as a ready-made cloud service, ideally with EU data residency.

4) Hybrid
Meaning: One part of the processing remains internal / local / in a private cloud, while another part runs in an external cloud or EU SaaS.

5) AVV / DPA
Meaning: This is the data processing agreement or Data Processing Addendum. It governs that the provider processes personal data on behalf of the customer and is bound by the customer's instructions.

6) No training
Meaning: The provider does not use your prompts, uploads, attachments, chat histories, or outputs for training or improving the general model — ideally excluded by contract.

7) Open-source / transparency path
Meaning: There is a path toward greater technical transparency and sovereignty, for example through:
- open models
- documented components
- self-hostable parts
- traceable architecture
- export / switching options

✅ = well covered ⚠️ = partial / indirect ❓ = not available / unclear
On-prem / local hosting
Private cloud / data center ⚠️
EU SaaS / Managed ⚠️
Hybrid ⚠️
DPA / AVV
No training on customer data
Open source / transparency path

On-prem / local hosting: covered

Covered because the website explicitly describes an on-premises/self-hosting option for the core technology. The development page states that anyone can run their own LanguageTool server locally or in the cloud; company documentation also mentions an on-premises version.

Private Cloud / Data Center: Partially

Partially, because EU/German infrastructure and multiple hosting providers are mentioned, but there is no clear description on the website of a dedicated private cloud or isolated customer environment as a standard offering. Controlled operation can be inferred through self-hosting in one’s own cloud.

EU SaaS / Managed: Partially

Partially, because the website mentions EU-relevant hosting locations such as Germany and Ireland, and one PDF even claims that servers are located exclusively in Germany. At the same time, the privacy policy for service use also mentions the U.S., so a purely EU/EEA data residency for the SaaS variant is not consistently documented.

Hybrid: Partially

Partially, because according to the integration document, the widget works with both the cloud and on-premises solutions. This demonstrates technical compatibility, but an explicitly described hybrid operating model with a clear division of processing is not detailed on the website.

DPA: Covered

Covered, because a public DPA/AVV is available and it explicitly states that it meets the mandatory requirements for designating a data processor under Article 28 of the GDPR.

No training: covered

Covered because the privacy policy explicitly states that LanguageTool does not use user input to train its language algorithms or models, and that this is a default setting requiring no opt-out.

Open Source / Transparency Path: Covered

Covered, because the core functionality is described as open source, and the website explicitly allows users to run their own servers locally or in the cloud. This establishes a clear path to transparency and control.

Data Processing

The website presents a mixed picture regarding data processing: There are documented EU-based or German hosting options and a clear self-hosting path, but for standard use, recipients and processing locations in the U.S. are also listed. The DPA lists subprocessors with specific functions, including Telekom Germany, Hetzner, AWS Germany, Google Cloud Platform in Dublin, Cloudflare, as well as OpenAI and Aleph Alpha for rewriting tasks. For transfers outside the EU/EEA, the DPA refers to appropriate transfer mechanisms such as the Data Privacy Framework and Standard Contractual Clauses.

Conclusion

For users in Europe, LanguageTool is generally best evaluated through the on-premises/self-hosting option: This is clearly documented on the website and enables significantly more controllable GDPR-compliant use within EU/EEA infrastructure. The standard SaaS offering is better documented in terms of data protection than many other tools, but due to the explicitly stated connections to the U.S. and the lack of a clear guarantee that data will be stored in the EU as standard, it is not as secure as the self-hosted version.

Sources

On-prem / local hosting
Private cloud / data center ⚠️
EU SaaS / Managed ⚠️
Hybrid ⚠️
DPA / AVV
No training on customer data
Open source / transparency path

On-prem / local hosting: covered

Covered because the website explicitly describes an on-premises/self-hosting option for the core technology. The development page states that anyone can run their own LanguageTool server locally or in the cloud; company documentation also mentions an on-premises version.

Private Cloud / Data Center: Partially

Partially, because EU/German infrastructure and multiple hosting providers are mentioned, but there is no clear description on the website of a dedicated private cloud or isolated customer environment as a standard offering. Controlled operation can be inferred through self-hosting in one’s own cloud.

EU SaaS / Managed: Partially

Partially, because the website mentions EU-relevant hosting locations such as Germany and Ireland, and one PDF even claims that servers are located exclusively in Germany. At the same time, the privacy policy for service use also mentions the U.S., so a purely EU/EEA data residency for the SaaS variant is not consistently documented.

Hybrid: Partially

Partially, because according to the integration document, the widget works with both the cloud and on-premises solutions. This demonstrates technical compatibility, but an explicitly described hybrid operating model with a clear division of processing is not detailed on the website.

DPA: Covered

Covered, because a public DPA/AVV is available and it explicitly states that it meets the mandatory requirements for designating a data processor under Article 28 of the GDPR.

No training: covered

Covered because the privacy policy explicitly states that LanguageTool does not use user input to train its language algorithms or models, and that this is a default setting requiring no opt-out.

Open Source / Transparency Path: Covered

Covered, because the core functionality is described as open source, and the website explicitly allows users to run their own servers locally or in the cloud. This establishes a clear path to transparency and control.

Data Processing

The website presents a mixed picture regarding data processing: There are documented EU-based or German hosting options and a clear self-hosting path, but for standard use, recipients and processing locations in the U.S. are also listed. The DPA lists subprocessors with specific functions, including Telekom Germany, Hetzner, AWS Germany, Google Cloud Platform in Dublin, Cloudflare, as well as OpenAI and Aleph Alpha for rewriting tasks. For transfers outside the EU/EEA, the DPA refers to appropriate transfer mechanisms such as the Data Privacy Framework and Standard Contractual Clauses.

Conclusion

For users in Europe, LanguageTool is generally best evaluated through the on-premises/self-hosting option: This is clearly documented on the website and enables significantly more controllable GDPR-compliant use within EU/EEA infrastructure. The standard SaaS offering is better documented in terms of data protection than many other tools, but due to the explicitly stated connections to the U.S. and the lack of a clear guarantee that data will be stored in the EU as standard, it is not as secure as the self-hosted version.

Sources

Strengths & weaknesses at a glance

Strengths Weaknesses
– Very clear focus on writing, correcting, and improving style. – Not a full-fledged research or general AI assistant; LanguageTool describes itself more as an AI Editing Tool than an AI Writing Tool.
– 30+ languages and dialects, particularly strong in English, German, Spanish, French, Dutch, and Portuguese. – According to the current Help Center, the browser extension is now only available for Premium.
– Many integrations: browser, Word, Google Docs, LibreOffice, mail clients, desktop. – The practical value increases significantly with Premium; the free version is clearly limited.
– Open-source core, self-hosting, and API make the tool unusually flexible. – Although data protection is comparatively well documented, the current data controller is Learneo, Inc. in the USA, which means international data transfers remain relevant.
– Positive for data protection: no use of user inputs for model training, DPA available, on-premise possible. – According to official communication, language quality and additional checks are more developed in some major languages than in all peripheral languages.

Data last updated: 16. April 2026

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