4 Steps for Building Event-Driven GenAI Applications

This article discusses how companies can build GenAI-enabled applications using a combination of foundation models like LLMs, data streaming platforms, and event-driven patterns. The approach involves breaking down the application into four steps: data augmentation, inference, workflows, and post-processing, which are ideally implemented as separate event-driven services. This allows for scalability, independence, and real-time processing of data, making it possible to generate reliable results. A data streaming platform can help integrate disparate operational data across the enterprise in real-time, enabling businesses to route relevant data streams to anywhere they're needed. By embracing an event-driven methodology, companies can decouple systems, teams, and technologies, facilitating data products that are well contextualized, trustworthy, and discoverable, ultimately promoting data reusability, engineering agility, and greater trust.

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