About Inkognito

One person, one tool, and a very specific writing problem.

Inkognito rewrites AI-generated drafts so they read the way a person writes — uneven sentence lengths, ordinary word choices, the small imperfections that machine prose never has. It is built and run by Gabriel Kilonzi, operating as JuneTechSolutions in Nairobi, Kenya.

Who runs this

The person behind the tool

GK
Gabriel Kilonzi

Founder, developer, and the author of everything published on this site — the guides, the blog, the prompt design, and the scoring logic. I write the product copy and the engine prompts myself, which is why the two agree with each other.

Inkognito is operated as a solo project under the trading name JuneTechSolutions. It is not yet an incorporated company; registration as an LLC is in progress, and this page will be updated with the registration details once that completes. I would rather tell you that than print a company number that does not exist.

Nairobi, Kenya junetechsolutions@gmail.com

There is no support desk and no outsourced inbox. Emails and contact form messages come to me, and I answer them — usually within a working day, occasionally slower when Nairobi and your timezone disagree.

Our story

Why this exists

The tool started because of a flagged paper. A draft that had been researched, argued and written by a human — with an AI assistant used for the boring connective tissue, the transitions and the abstract — came back from a university detection tool marked as machine-written. Nothing was plagiarised. Nothing was fabricated. The argument was original. What gave it away was the cadence: every sentence landing in the same twenty-word range, every paragraph opening with a signpost, not a single clumsy turn of phrase anywhere.

That is the part most people misunderstand about AI detection, and it is the reason this tool works the way it does. Detectors are not reading for meaning, honesty, or effort. They are measuring statistical regularity — how predictable each next word is, and how little the sentence lengths vary. Perfectly clean writing scores as machine writing. Which means the fix is not a thesaurus. The fix is rhythm.

Most humanizers never got that memo. They swap "utilize" for "use," sprinkle in a contraction, and hand the text back. That is itself a pattern, and a detector picks it up as easily as the original. Inkognito was built around the opposite premise: leave the vocabulary mostly alone and rebuild the structure.

How it works

The method, in plain terms

Your text goes through four stages. None of them invent new material — that is a hard rule in the engine prompts, not a marketing line.

  1. 1. Protection pass

    Before anything is rewritten, the text is scanned for things that must survive untouched: URLs, in-text citations, statistics and percentages, proper nouns, dates, currency figures, and quoted passages. Each is locked behind a placeholder so the rewriting model physically cannot alter it. This is why a rewritten bibliography still cites the same page numbers.

  2. 2. Structural rewrite

    The rewrite is sentence-by-sentence, in the same order, at roughly the same length — the engine is instructed to stay within about 95–105% of your original word count. What changes is shape: long sentences get split, parallel three-part lists get broken, signposted transitions ("Furthermore," "In conclusion,") get dropped, and paragraph rhythm is varied deliberately so that no two paragraphs follow the same template.

  3. 3. Scoring

    The result is scored for how human it reads. Sections that still look uniform are flagged individually rather than the whole document being thrown away.

  4. 4. Targeted rescue

    Flagged sentences are rewritten again, each with a different corrective move — split, merge, reorder, deflate, front-load — chosen so the repairs themselves do not become a detectable pattern. Then a light cosmetic pass removes repeated hedge words. That is why scores hold up in long documents instead of decaying after the first few paragraphs.

If you want the applied version of this, the Turnitin guide walks through the same ideas with worked before-and-after examples.

What we stand for

Four commitments

Your text is not training data

Inputs and outputs are stored on your account so your dashboard history works, and nothing else. They are never sold, shared, or used to train a model. Delete a single run or your whole history whenever you like — see the privacy policy.

Meaning is not negotiable

The engine rewrites style and rhythm, never substance. Facts, arguments, statistics and citations come through intact — and the protection pass enforces it mechanically rather than trusting the model to behave.

Numbers we publish are measured

Every success rate quoted on this site comes from our own eval runs on our own samples, and we say so next to the number. We do not publish figures we have not produced ourselves, and we do not invent testimonials.

Read-aloud test

If a rewrite does not survive being read out loud, it does not ship. A high score on text nobody would want to read is not a result worth having.

Honest limits

What Inkognito is not

It is not a guarantee. No detector outcome is promised, here or anywhere on this site. Detection models retrain, sometimes monthly, and the same passage can be judged differently by two tools on the same day. Any service promising permanent undetectability is selling you something it cannot deliver.

It is not affiliated with any detector. Turnitin, GPTZero, Originality.ai, Copyleaks, ZeroGPT, Winston AI and Sapling are independent products and trademarks of their owners. We test against them; we have no relationship with them.

It is not a licence to cheat. Plenty of institutions prohibit AI assistance outright, and that is their call to make. Using this tool to misrepresent authorship where it is banned breaks our terms of service, and the consequences land on you, not on us.

It is not a writing service. The engine will not add an argument you did not make, an example you did not give, or a paragraph you did not write. It is most useful once you already have something to say and just need it to sound like you said it.

Where to go next

If you are deciding whether this fits your work, the use cases page covers who actually uses it and how. If you want the reasoning behind the engine, the journal is where the longer arguments live.