Artificial intelligence video analyzer for compliance assessment

A computer-implemented method for determining whether video content conforms to organizational policies and legal requirements, the method comprising:

• obtaining, by a computing system, a video data stream comprising a sequence of image frames and associated audio;
• transforming, by the computing system, the obtained video data stream by:
• reducing frame-to-frame motion artifacts to stabilize the image sequence;
• normalizing luminance and color distribution across frames to achieve temporal lighting consistency;
• and
• suppressing non-speech audio components to reduce acoustic interference in downstream speech analysis;
• extracting, by the computing system, a plurality of features from the transformed video data stream, the features comprising:
• visual content derived from analyzing pixel-level patterns across a sequence of frames using a convolutional neural network;
• audio-derived textual content obtained via speech-to-text conversion using a deep recurrent or transformer-based sequence model;
• and
• embedded or overlay text extracted using optical character recognition techniques;
• evaluating, by the computing system, the plurality of features with respect to a plurality of compliance rules by applying one or more trained machine learning models to detect patterns indicative of potential violations, the trained models configured to capture semantic, contextual, and cross-modal relationships between extracted content and predefined policy constraints;
• and
• constructing, by the computing system, an output data structure comprising an assessment of whether the video content conforms to the plurality of compliance rules, the output data structure identifying nonconforming segments and providing time-aligned annotations corresponding to the detected nonconformities.