Empowering researchers and journalists with intelligent, context-aware misinformation detection using advanced NLP models.
Designed for precision, scalability, and clarity.
Uses a 60/40 weighted ensemble of BERT and TF-IDF models to analyze both meaning and statistical patterns.
Advanced strategies fetch clean article content from any URL, automatically ignoring ads and metadata.
Transparent factor breakdowns show exactly why an article was flagged, providing human-readable evidence.
Your analysis history is stored securely in SQLite, allowing for narrative tracking over time.
Handle entire datasets at scale. Predict across thousands of rows with optimized pipeline execution.
Rich visualizations including radar charts and trust gauges make data interpretation intuitive.
A seamless transition from raw URL to validated data.
Scrape URL or input text.
BERT & TF-IDF Analysis.
Consensus logic applied.
Final trust score & XAI.