Real-time data is crucial for generative AI because it ensures that large language models (LLMs) have access to current and contextual information. This allows businesses to provide accurate and relevant responses tailored to specific situations, enhancing the overall effectiveness of AI applications.

Companies can integrate domain-specific knowledge into LLMs through two main approaches: prompt engineering, which optimizes input for better accuracy, and fine-tuning, which involves retraining models on specific datasets. Both methods help ensure that the AI understands and responds appropriately to industry-specific queries.

Data streaming platforms enhance generative AI applications by providing real-time access to data across the organization. They break down data silos, ensuring that relevant information is available when needed, which helps businesses deliver timely and sophisticated customer experiences while maintaining data governance and security.