Why Real-Time Data Architecture Is the Cornerstone of AI Success

Aerospike Founder and CTO Srini Srinivasan outlines how real-time data architecture empowers CxOs to scale AI, elevate customer experience, and lead in the AI-driven enterprise era.

- Shrikanth G

Srini V. Srinivasan Co-founder and CTO, Aerospike

For C-level leaders worldwide, the challenge lies in making sense of the AI disruption. Many are exploring use cases while struggling to align AI with broader business goals. The biggest ‘make or break’ factor? It’s Data, and how it’s been handled so far, how it’s used for AI, and the data systems in place.

In this context, Srini Srinivasan, Co-founder and CTO of Aerospike, offers a grounded perspective: AI only works if your data systems can keep up, with speed, consistency, and scale.

Aerospike supports some of the most data-intensive workflows in the world, whether it’s powering UPI-level throughput or enabling Flipkart’s Big Billion Days. As AI evolves, Aerospike’s role in data infrastructure becomes increasingly vital.

THE REAL SHIFT: FROM BATCH THINKING TO REAL-TIME EXECUTION

"Many systems were batch because they had to be," Srini says. "Legacy databases couldn't keep up with real-time ingestion or processing. But that has changed." With modern data infrastructure like Aerospike, paired with event-streaming platforms like Kafka, organizations no longer need to choose between scale and speed. Real-time isn’t just possible, it’s essential.