WasItAIGenerated wasitaigenerated.comCan AI replace WasItAIGenerated?
The interface is a text box; the product is a fine-tuned classifier. Detection quality does not come from a clever prompt. It comes from training a model on a labelled corpus and tuning it until the error rate is low enough to act on, which is months of work against a target that moves every time a new generator ships. Asking a general model "is this AI-written?" produces confident, unreliable answers, and in an academic-integrity setting that means falsely accusing real students. A one-shot build gets you the UI and none of the responsibility.
01What it costs
Checked Aug 12, 2026 · source: wasitaigenerated.com.
| Plan | Monthly | Billed yearly | What you get |
|---|---|---|---|
| Starter | Free | Free | 1,000 credits after email verification; text costs 1 credit/word, image 300 credits, audio/voice 1,000, video 2,000. |
| Unlimited Website | $9.99 | — | Unlimited website detections across text, image, audio, and video; API access not included. |
| Starter Pack | — | — | 40,000 API credits; credits never expire. |
| Credit Package | — | — | 200,000 API credits; credits never expire; bulk/API access. |
Hidden costs: The $9.99 website subscription does not include API use; API calls consume separately purchased credits.
02Could AI build it for you?
The core job: Build a private workspace that pastes in text, asks one general model for an AI-likelihood judgement with reasoning, stores results, and exports them.
What a working version needs:
- OpenAI or Anthropic API key in .env
- Node.js 22
- SQLite database
- A README stating plainly that the output is a guess, not a detector, and must never be used to accuse anyone
The text box is trivial. The trained classifier and its measured false-positive rate are the product.
03What you'd give up
- a trained classifier and the labelled corpus behind it
- a measured false-positive rate you can quote to an institution
- detection for images, audio and video, not just text
- per-sentence highlighting instead of one document-level guess
- retraining as generators change
Institutions do not buy a verdict, they buy a defensible one. A university that flags a student needs a documented error rate, an audit trail and a vendor who will stand behind the number. That is a measurement problem, not an interface problem, and it is why every serious buyer in this category asks about false positives before features.
04The build prompt
Read the verdict first: this one is hard to get right.
The complete build prompt, plus 11 step-by-step prompts from research to launch, a design system file, a page-by-page spec, the data model and a launch checklist.
Get the Build Kit · $9 →One-time payment. Delivered on screen and by email.
05Free open-source starting points
- Binoculars: Zero-shot LLM text detection using perplexity ratios between two models.
- DetectGPT: Curvature-based zero-shot detection of machine-generated text.
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Prices change; confirm on the vendor's site before you decide.
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