ShaScam leverages cutting-edge technologies to protect users from phishing and spam calls in real-time. By integrating Twilio's API for call management and Google Cloud's speech-to-text for live call transcription, alongside advanced LLM inference with a Mixtral-8x7B model, ShaScam provides an innovative defense mechanism against the rapidly evolving threat landscape of scam calls.
- Real-time Scam Analysis: Utilizes Twilio for call routing and Google Cloud for transcription, analyzing conversations in real-time to detect scam likelihood.
- Intelligent Call Filtering: Employs a Mixtral-8x7B model for dynamic analysis of call content, offering immediate risk assessment and response recommendations.
- User-Centric Design: Offers a simple, intuitive interface for managing Twilio proxy numbers and receiving instant alerts on potential scam calls.
- Data Acquisition: Faced with the scarcity of quality spam call datasets, we navigated through various sources to compile a viable dataset for model training and validation.
- Model Accuracy: Addressed challenges in model generalization and overfitting by opting for a higher-parameter Mixtral-8x7B model and refining our dataset for enhanced precision in scam detection.
- User Privacy and Autonomy: Implemented Twilio proxy numbers to maintain user privacy and control over call monitoring, ensuring compliance with data collection and privacy standards.
- Enhanced Scam Trend Analysis: Developing capabilities to categorize and analyze scam trends for personalized user alerts.
- Model Fine-Tuning: Continuous improvement of the LLM's accuracy through the acquisition and incorporation of diverse and high-quality data sets.
ShaScam represents a significant step forward in the use of AI and real-time data processing for scam call detection and prevention, offering users a proactive tool against potential security threats.
Built with ❤️ by Nitya Arora, Tanush Chopra, Sahil Gupta, and Darius Kianersi.