We run AI detectors against real student essays and publish every result, failures included. How we test →
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If you are building an LMS plugin, an admissions pipeline, or an internal grading tool, you need an AI detector API, not a paste box. This page compares the developer offerings of the vendors we track, with one discipline up front: our August 2026 test round exercised web scanners, not API endpoints, so every capability claim below comes from official documentation and is labeled that way. Verify against current docs before you write a line of integration code.
Who Offers a Real API
Plenty of detector sites are web-only products with a contact form where the API should be. The vendors below advertise documented developer access on their official sites as of August 2026.
Docs-Based Pick
O
Originality.ai
Scan pipelines + paraphrase
Not rated (docs-based)
REST API with per-credit pricing, per official documentation
Sentence-level results and paraphrase detection documented
Strong third-party accuracy ratings; we did not call the API ourselves
How we rate: stars combine measured performance and reliability in our August 2026 test rounds. Tools we could not run hands-on are marked Not rated (docs-based).
Winston AI and ZeroGPT also list API access on their sites; Pangram sells institutionally and documents integrations. We have not exercised any of these endpoints, so no latency or throughput claims from us.
The Integration Checklist
Before committing to an AI detector API, pin down five contract-level details:
Pricing at your volume. A credit model that looks cheap at 1,000 words a day behaves differently at an admissions cycle’s 50,000 essays. Model your peak month, not your average.
Length limits per call. Essays fit easily; theses and manuscripts may not. Check maximum characters per request and whether long documents get chunked or truncated.
Response granularity. A single document-level probability is hard to act on. Sentence-level spans (documented by Originality.ai) let you show a reviewer exactly which lines triggered the flag.
Paraphrase handling. Rewritten AI text is the input that matters most in education. Third-party tests find it the hardest category; only some vendors document detection for it.
Data retention. If the payload is student work, retention and training-use clauses are legal questions, not engineering ones. Get the vendor’s terms in writing before the first production call.
Vendor
API documented?
Paraphrase detection
Free tier for API?
Entry pricing
Originality.ai
Yes, per official docs
Yes, per official docs and third-party tests
Limited trial credits
~$14.95/mo
Copyleaks
Yes, per official docs
Partial, per vendor claims
Limited free scans (web)
~$11/mo
GPTZero
Yes, per official site
Weak per third-party tests
No; free plan is web-only
~$15/mo
Winston AI
Listed on site
Partial, per vendor claims
14-day trial, 2,000 words
~$12/mo
Whichever AI detector API you pick, validate it against your own corpus before launch: fifty known-AI texts, fifty known-human texts, and a batch of paraphrased samples. Our how AI detectors work explainer covers why scores are probabilities, and the tested ranking shows what a hands-on round looks like when vendors are put against real essays.
Per official documentation: Originality.ai, Copyleaks, GPTZero, and Winston AI advertise developer APIs, and ZeroGPT lists API access. We did not call any endpoint hands-on this round, so verify against current docs before building.
What should I check before integrating an AI detector API?
Per-request pricing at peak volume, length limits per call, sentence-level versus document-level responses, documented paraphrase handling, and data retention terms. Then validate with your own known-AI and known-human samples.
Is there a free AI detector API?
Fully free API tiers are rare. GPTZero’s official free plan is a web product, not an API allowance. For prototypes, an entry paid tier usually costs less than engineering around a free web scanner’s rate limits.
How accurate are AI detector APIs on student writing?
Probabilistic, with a known bias: a 2023 Stanford-led study in Patterns found detectors flag non-native English writing far more often. Build human review into any education workflow and never auto-penalize on one score.