Elad Bernstein

Modern algorithmic trading platforms deploy fleets of specialized AI agents, including market analysts, risk assessors, order executors, and compliance monitors, that must coordinate in real time without conflict.

Semantic caching uses vector similarity search to retrieve cached LLM responses for semantically equivalent queries, reducing inference latency and cost in agentic AI architectures.

Building highly scalable, high-performance AI and data-driven applications requires intelligent caching strategies. In this session, learn how to build with Amazon ElastiCache to scale workloads across caching patterns such as session caching, KV-caching, and more.

In this builders' session, you will create a high-performance, real-time, geospatial alerting pipeline using Amazon ElastiCache for Valkey. This architecture pattern is tailored for dynamic applications like ridesharing, logistics, and fleet management.

Learn how to build highly scalable, high-performance applications with Amazon ElastiCache Serverless. View how ElastiCache Serverless works behind the scenes and dive deeper into the metrics to help you identify and debug application performance issues.

Imagine a world where every customer call is answered instantly, issues are resolved swiftly without any human intervention, and the entire experience feels personal and seamless.