AI detector for Content Managers

1. 1

   Set content policy (acceptable AI use, disclosure requirements, quality bar)

2. 2

   Configure AI Checker thresholds for your team

3. 3

   Run incoming content through batch API or web interface

4. 4

   Surface high-AI-score content for revision or rejection

5. 5

   Track team-level AI-content trends in dashboard reporting

The content managers use case, in detail.

Content managers sit at the intersection of editorial standards, team management, and platform compliance — and AI detection is increasingly part of all three. The hardest challenge isn't catching obvious AI; it's setting and communicating a coherent policy that your team can actually follow. AI Checker's team accounts include configurable thresholds (so you can set, say, 60% as the editorial flag), per-author tracking (so you can see if a specific freelancer's work is drifting AI-ward over time), and team-level reporting that surfaces trends without singling out individuals. The dashboard is designed to support productive conversations with your team rather than punitive enforcement: most cases of high-AI scoring are resolved with a quick conversation about disclosure and editing, not termination. Enterprise tiers include SSO, audit logs, and on-premise deployment for regulated industries.

The content managers workflow, in depth.

Content management has shifted from a coordination job to a policy-design job over the past two years, largely because of AI tools. The content manager who used to schedule deliverables and align brands now also has to write the AI-use policy, communicate it to a distributed team, monitor compliance without surveilling, and adjust the policy as both AI capabilities and platform expectations evolve. AI Checker's team tier is designed for this expanded role. The tooling supports policy enforcement without requiring micro-management. Configurable thresholds mean different content types can have different AI-acceptance ranges (long-form thought leadership held to a higher bar than weekly newsletter copy, for example). Per-author tracking surfaces trends — Drift AI-ward over time often signals a writer using AI more heavily under deadline pressure, which is a workflow conversation rather than a compliance violation. Team-level reporting aggregates trends without singling out individuals, so leadership can see the overall picture without the data feeding into punitive enforcement. The dashboard is intentionally designed to support productive conversations: most cases of high-AI scoring resolve through a quick conversation about disclosure and editing, not through termination. The hardest part of the job — setting and communicating a coherent policy your team can actually follow — is the part AI Checker provides templates and example language for. Common policies that work in practice: "AI assistance is permitted for research, structuring, and proofreading; AI drafting is permitted only with disclosure; final published copy must score under 50% AI on review." Enterprise tiers include SSO via Okta or Azure AD, audit logs that meet major compliance frameworks, and on-premise deployment for regulated industries (healthcare, financial services, government). Privacy commitment: per-author tracking data stays within your team account; we do not aggregate author-level patterns across customers.

Built for content managers 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.