CensorX is an AI Business tool. Detects and filters explicit content in images and text with AI. Key features include Vision Transformer (ViT) Image Detection, DistilBERT Text Classification, and Sub-100ms Latency. Best for software developers and engineers, social media managers and content creators.
About CensorX
CensorX is an AI content moderation API designed to detect NSFW content in images and text in real time. The platform serves as backend infrastructure for social media platforms, e-commerce sites, gaming platforms, and other services that need to filter user-generated content before it reaches other users.
The core features that matter
- Vision Transformer (ViT) image detection with 91.9% accuracy and 0.99 AUC score for distinguishing safe from explicit images across diverse content types
- DistilBERT text classification trained on 200,000 examples for detecting offensive language with high precision, supporting content moderation at scale
- Sub-100ms latency for moderation that runs in real time, suitable for live chat applications and other latency-sensitive contexts
- Multimodal capabilities handling both text and image content simultaneously, providing unified moderation across content types in one API call
- Self-hosting option with model weights freely available on Hugging Face, supporting deployments where data sovereignty or cost control matters more than managed convenience
- API integration through RapidAPI for the managed version, providing easy adoption without infrastructure setup
How it stands out
The content moderation API space has established commercial players (Sightengine, Hive Moderation, AWS Rekognition Content Moderation) plus open-source alternatives. CensorX's specific positioning combines open-source availability (self-hosting through Hugging Face) with a managed API option, giving users the flexibility to choose based on their specific cost, performance, and data handling needs.
The honest qualifier: content moderation accuracy claims from any provider need careful interpretation. 91.9% accuracy sounds high but means roughly 1 in 12 items get classified incorrectly. A meaningful false positive or false negative rate depending on context. For large-scale moderation where you accept some misclassification and use the API as a first filter before human review, CensorX provides solid signal. For high-stakes contexts where false negatives are unacceptable, multiple detection systems alongside human review remain necessary.
Key Features
Vision Transformer (ViT) Image Detection.
DistilBERT Text Classification.
Sub-100ms Latency.
Multimodal Capabilities.
Self-Hosting Option.
API Integration.
Frequently Asked Questions
CensorX's DistilBERT model understands the nuances of language. It looks at the sentence structure to tell if something is offensive or not, instead of just matching keywords.
The vision model works best with regular photos. If you use AI-generated or highly stylized images that weren't part of its training, the accuracy might go down.
For text, CensorX responds in under 100 milliseconds. For images, it can process about 52 images every second.
If you self-host CensorX, your data is processed locally and not stored externally. For the managed service on RapidAPI, content is usually deleted soon after it's processed.
