Real-time agent assist is revolutionizing contact centers by leveraging AI technologies such as speech recognition, natural language processing (NLP), and intelligent automation to provide immediate guidance and information during live customer interactions. Unlike traditional methods that analyze calls post-conversation, real-time systems offer instant recommendations by continuously monitoring discussions to extract intent, sentiment, and key topics. This system acts as an AI copilot, enhancing agent capabilities, reducing information overload, and improving customer satisfaction by allowing agents to access relevant information without delay. Key benefits include improved customer ratings, reduced agent stress, and proactive management of emerging issues by contact center managers. The technology stack for real-time agent assist requires precise orchestration of various AI components under tight latency constraints, with challenges such as maintaining conversational context, integration complexity, and ensuring compliance. As the technology evolves, future developments may include multimodal assistance, predictive features, and more natural conversational AI interactions, making these capabilities increasingly accessible to a broader range of organizations.