As modern systems scale, performance bottlenecks and inefficiencies can cripple even the most advanced architectures. This session explores how artificial intelligence can be strategically integrated into backend systems to automate optimization, predict system load, and enhance performance in real time.

Raghav Sood will walk participants through practical AI-driven techniques for workload prediction, query optimization, and anomaly detection — with a focus on cost efficiency and scalability. The talk blends research insights with hands-on applications, showing how AI models can assist in database tuning, API latency reduction, and intelligent caching strategies.

Attendees will gain a comprehensive understanding of how to bridge the gap between backend engineering and applied machine learning — not just as a concept, but as a deployable performance enhancer. Whether you’re building large-scale distributed systems or optimizing microservices, this session provides actionable insights to future-proof your backend architecture.