AI detector for Marketers

1. 1

   Receive content from agency, freelancer, or in-house team

2. 2

   Batch-check via AI Checker API or paste individual pieces

3. 3

   Review the AI probability scores against contract or policy expectations

4. 4

   Surface AI-heavy pieces for revision or re-attribution

5. 5

   Apply Google E-E-A-T compliance checks for SEO content

The marketers use case, in detail.

Marketing teams use AI detection for two reasons: SEO compliance (Google's Helpful Content Update penalizes low-effort AI content) and contract compliance (verifying agency deliverables match the human-written deliverables paid for). The SEO use is increasingly important — Google's quality raters explicitly look for AI-generated thin content, and entire sites have been deindexed for relying on it. AI Checker's batch API lets marketing ops audit weeks of content output in a single sweep, with sentence-level breakdown highlighting the specific pieces that need revision before publication. For agency relationships, we provide a verification report that documents AI-content percentages over a billing period — useful for contract compliance documentation. Our recommendation: don't ban AI assistance, but require sentence-level human revision so output scores cleanly human on detection tools.

The marketers workflow, in depth.

Marketing operations has become a major use case for AI detection through two converging pressures: Google's increasingly aggressive enforcement of the Helpful Content Update against low-effort AI-generated content (entire sites have been deindexed for relying on thin AI text), and the contract-compliance question of whether content agencies are delivering the human-written work they're paid for. AI Checker's marketing tier addresses both. The SEO compliance workflow is the higher-volume use: batch-scan every piece of content output (blog posts, email copy, landing pages, sponsored content) before publication, flag pieces that score above your editorial threshold, route them back for sentence-level revision, and re-check before publishing. Marketing teams using AI Checker this way report sustained organic traffic above pre-AI-era baselines because their content survives HCU rounds that competitors fail. The contract-compliance workflow is lower-volume but higher-leverage: at the end of each billing period, run all agency deliverables through AI Checker and compare actual AI-content percentages against the contract terms. Many content-agency contracts now include explicit AI-use clauses ("deliverables shall be human-written with AI assistance limited to research and editing"), and AI Checker's verification reports document compliance over the billing period. For brand-side teams managing in-house content, AI Checker also surfaces author-level trends: which writers are drifting AI-ward over time, which content categories are most AI-vulnerable, which topics are seeing the most AI-assisted submissions. Our recommendation for most marketing teams: don't ban AI assistance — that's unrealistic and counterproductive — but require sentence-level human revision so output scores cleanly human on detection tools. This produces better content for readers and survives HCU rounds simultaneously.

Built for marketers 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.