This paper presents Lexa AI, a holistic AI-powered solution for improving criminal investigative practices through four phases, that target key drawbacks found in traditional practices. The first model provides an automated data/information collection stage that accepts legal documents in multiple formats that utilize a three-stage processing pipeline based on Gemini 2.0 Flash model, which performs Optical Character Recognition (OCR) with a higher level of accuracy and speed compared to alternative approaches. The collected data will be escalated to the next phase by leveraging dynamic question generation that uses Reinforcement Learning (RL), instantaneous multilingual capacity, and real time scoring of relevance. In the third phase Multimodal Behavioral and Physiological Analysis (MBPA) will be done, which includes facial signals, speech signals, and heart rate signals to create a combined Stress Index as an objective indicator, and without judgement. Finally, semantic similarity will be measured to correlate incidents, assess risk for victims, and provide explainable predictions.

Automated Data Collection,Machine Learning,Law,Legal Technology,Criminal Invest,Artificial Intelligence