Clarifai

The API covers image and video prediction (using pre-built or custom models), text classification, model training, and concept management. The prediction API is the primary agent integration surface — agents submit image URLs or base64 content and receive classification results with confidence scores. The custom model workflow enables teams to label domain-specific acceptable/unacceptable content and train models that reflect their community standards.

Reliability is production-grade for AI inference infrastructure. Clarifai maintains the availability required for real-time moderation use cases where content blocking decisions need to happen before publication. Async processing options are available for batch moderation workflows where real-time response is not required.

Clarifai is an AI platform with strong content moderation capabilities covering both visual (image, video) and text content. Its pre-built moderation models cover explicit content, unsafe content, and text toxicity, while its custom model training enables teams to define domain-specific moderation rules beyond the standard categories. For agents moderating user-generated content at platforms where standard moderation models don't cover the content domain adequately, Clarifai's custom training capability is the relevant differentiator.

Authentication uses API keys tied to Clarifai applications. Each application has its own key, enabling per-use-case access control and usage tracking. Teams should use separate Clarifai applications for different moderation use cases or environments to maintain independent key management and usage monitoring.

Documentation is comprehensive and covers the prediction API and custom model training workflow clearly. The concept management documentation — explaining how to define and train custom content categories — is particularly relevant for teams building domain-specific moderation. Teams building agent-driven content moderation pipelines on Clarifai will find the documentation covers both the pre-built and custom model paths.