Our mission is to create safer digital spaces through AI-powered toxicity detection.
Using state-of-the-art NLP models, we analyze text for toxic patterns including cyberbullying, hate speech, and offensive language.
Each analysis returns a confidence percentage indicating how likely the content is to be toxic, helping you make informed decisions.
All your analyses are stored securely for your reference, with no data shared externally.
CyberGuardian leverages the unitary/toxic-bert model from Hugging Face's Transformers library, a state-of-the-art deep learning model fine-tuned specifically for toxicity detection.
The model analyzes text across multiple dimensions including:
With an accuracy rate exceeding 90% on benchmark datasets, our system provides reliable detection while minimizing false positives.
Screen user-generated content before posting to maintain positive community standards.
Monitor school forums and messaging platforms to prevent cyberbullying among students.
Maintain professional standards in internal communications and collaboration tools.
Filter toxic chat messages to create more inclusive gaming environments.