A Scalable, Event-Driven Architecture for High-Volume Document Ingestion and Real-Time AI Processing

The migration of enterprise agreement and document management systems towards intelligent automation (IA) necessitates robust architectures capable of handling massive ingestion volume while ensuring data integrity and low-latency AI model inference. This paper introduces an event-driven, microservices-based architecture designed to decouple high-volume document ingestion from asynchronous, computationally intensive AI processing workflows. By leveraging Apache Kafka as a durable event backbone and adopting a specialized, fault-tolerant worker service model, the system achieved a validated throughput of over one million documents per 24-hour cycle and demonstrated a 10x improvement in computational resource efficiency compared to traditional batch processing methods. This design provides a blueprint for scalable, compliant, and reliable information systems crucial for next-generation digital transformation.