AI detector for Developers

1. 1

   Get AI Checker API key (free tier)

2. 2

   Send text to /v1/detect endpoint

3. 3

   Receive JSON response with score and sentence-level breakdown

4. 4

   Integrate score into your application logic

5. 5

   Handle rate limits and pricing tiers as you scale

The developers use case, in detail.

Developers integrating AI detection into applications need a stable API more than a polished UI. AI Checker's REST API exposes the same detection model that powers the web app, with a clean JSON contract: send text, receive `{ score, sentences: [{text, score, flags}], model_match, confidence }`. The free tier supports 100 requests per day for development and prototyping. Production use cases — content moderation pipelines, education LMS integrations, marketplace authenticity systems — typically run on the paid tier with rate limits scaled to traffic. The API supports streaming responses for very long inputs, batch endpoints for periodic audits, and webhook callbacks for asynchronous workflows. Documentation includes example clients in TypeScript, Python, Go, and Rust. We do not charge per detected AI; pricing is per-request regardless of result, so there's no incentive to flag aggressively.

The developers workflow, in depth.

AI Checker's API is built for developers who want stable, predictable detection in their own products rather than another wrapped UI on someone else's model. The contract is intentionally simple: POST text, receive a JSON response with the document-level score, an array of sentence-level scores with model-match attribution, and a confidence indicator. The same model that powers the web app powers the API; there is no quality difference between tiers, only rate-limit and feature differences. The free tier supports 100 requests per day, sufficient for local development and small-volume prototypes; production use cases — content moderation pipelines on large platforms, LMS integrations across school districts, marketplace authenticity systems for review platforms — run on the paid tier with rate limits scaled to traffic. The API supports three response patterns. Synchronous responses for short text (under 5,000 characters): typical latency is 200-400ms. Streaming responses for long text (5,000-50,000 characters): incremental sentence-level scores arrive as they're computed, useful for UX patterns where users see live progress. Batch endpoints for periodic audits: submit hundreds of documents in a single call, receive a webhook callback when scoring completes. Documentation includes maintained example clients in TypeScript, Python, Go, Rust, and (community-maintained) PHP and Ruby. Pricing is per-request regardless of detection result — we don't charge more when we flag — so there's no built-in incentive to over-detect, and the cost per request is predictable for budgeting. For teams with strict data handling requirements, the enterprise tier supports on-premise deployment, private VPC peering, and SOC 2-compliant audit logging. The API contract is versioned semantically; v1 is stable through at least 2027, with v2 in preview for users who want access to additional signal channels (per-sentence model-match probability distributions, training-distribution proximity metrics).

Built for developers who need actionable detection.

• Sentence-level breakdown. Every result includes per-sentence scoring with the most likely source model identified — so the output is actionable evidence, not just a single percentage.
• Free tier with no daily traps. Up to 10,000 characters per check, unlimited checks per day, no signup required. Paid tiers exist for volume and team features, not as a tax on the free experience.
• API access on every plan. Integrate detection into your existing workflow with a clean REST API. Documentation includes example clients in TypeScript, Python, Go, and Rust.
• Privacy-first by default. Submissions are processed in memory and not used to train models. No third-party advertising trackers. Read our security & privacy policy for the long version.
• Multi-model coverage. We detect ChatGPT, Claude, Gemini, Llama, Mistral, Microsoft Copilot, and emerging open-source variants — not just GPT.

Detection by model, comparison, and language.