ToHuman rewrites AI-generated content so it reads like a person actually wrote it — while keeping your original meaning fully intact. It runs its own fine-tuned Mistral 7B model rather than wrapping a third-party API, which keeps costs low enough for a genuinely free tier and means your text is never handed to an outside provider. It handles blog posts, essays, marketing copy, email, documentation, and academic writing, and offers a REST API for teams that process text at scale. Free plan: 2,500 words/month. Pro: $19/month for 100,000 words.

Hi Fazier! I built ToHuman after watching writers get flagged by AI detectors for text they had genuinely worked on — drafted with AI help, but edited, fact-checked, and made their own. Most humanizers in this space are thin wrappers around a general-purpose LLM API, so I went the other way: ToHuman runs its own fine-tuned Mistral 7B, tuned specifically for the humanization task. That's why the free tier can be genuinely free (2,500 words/month, no credit card) and why your text never leaves our infrastructure. There's also a full REST API with n8n, Zapier and MCP integrations for teams that process content at scale. Happy to answer anything about the model, the detector landscape, or the build!
Can i get you 1st rank on all the directories and even on your today launch on Fazier ✉️ Email: [email protected] 📱 Telegram: t.me/rforrank
ToHuman is a useful tool for making AI-generated content feel more natural, conversational, and human-like. At TeroTAM, it can be helpful for refining AI-assisted content for blogs, marketing materials, and other business communications, helping the final copy feel more engaging and less robotic while maintaining the original message.
The decision to run your own fine-tuned Mistral 7B instead of wrapping someone else's API is what makes this stand out to me — it's the difference between "your text never leaves our servers" being a real promise versus marketing. A free tier that's actually usable (2,500 words, no card) is rare in this category too. Would love to know how it holds up on more technical or jargon-heavy writing without flattening the meaning.

Hi Fazier! I built ToHuman after watching writers get flagged by AI detectors for text they had genuinely worked on — drafted with AI help, but edited, fact-checked, and made their own. Most humanizers in this space are thin wrappers around a general-purpose LLM API, so I went the other way: ToHuman runs its own fine-tuned Mistral 7B, tuned specifically for the humanization task. That's why the free tier can be genuinely free (2,500 words/month, no credit card) and why your text never leaves our infrastructure. There's also a full REST API with n8n, Zapier and MCP integrations for teams that process content at scale. Happy to answer anything about the model, the detector landscape, or the build!
Can i get you 1st rank on all the directories and even on your today launch on Fazier ✉️ Email: [email protected] 📱 Telegram: t.me/rforrank
ToHuman is a useful tool for making AI-generated content feel more natural, conversational, and human-like. At TeroTAM, it can be helpful for refining AI-assisted content for blogs, marketing materials, and other business communications, helping the final copy feel more engaging and less robotic while maintaining the original message.
The decision to run your own fine-tuned Mistral 7B instead of wrapping someone else's API is what makes this stand out to me — it's the difference between "your text never leaves our servers" being a real promise versus marketing. A free tier that's actually usable (2,500 words, no card) is rare in this category too. Would love to know how it holds up on more technical or jargon-heavy writing without flattening the meaning.
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