How Financial Service Companies Can Successfully Migrate Critical Applications to the Cloud (eBook)

The shift toward real-time decision-making at the edge is an evolution in how businesses operate. Closing the latency gap means smarter, safer, and more resilient operations.

AI agents represent an opportunity to go beyond isolated analytics projects and move toward self-improving, autonomous workflows that directly drive operational performance.

Scaling AI in industry requires the right technology, a practical understanding of industrial operations, and open interoperability with an organization’s existing data infrastructure.

The enterprise data stack is at an inflection point. Storing and streaming data is no longer enough. Businesses need a combination of streaming technologies, high-performance in-memory databases, and adaptive intelligence to support real-time enterprise operations.

To operationalize sub-second RAG, the author proposes the FLASH Framework (Fast Latency Architecture for Streaming Hybrid retrieval), a 4-step methodology distilled from deploying 50+ enterprise pipelines since 2024.

Far from accelerating Excel’s extinction, AI agents are extending Excel’s lifespan by making it more accessible and more powerful.

In this week’s real-time analytics news: The EuroHPC Joint Undertaking focuses on AI Gigafactories and sovereign AI.

Organizations that embrace event-driven architecture early will build more resilient, scalable, and maintainable AI systems. EDA enables greater resilience, scalability, and observability, which are essential for robust, enterprise-ready Agentic AI.