AI Agents, Real-Time Data & Modern Architectures

Join us for a day of learning and discussion around AI agents, real-time data, and modern system design. This meetup brings together engineers, architects, and developers to explore how today’s applications are being built using AI, fast data systems, and scalable architectures.

The sessions will cover practical patterns, real-world architectures, and live demonstrations — focusing on how AI agents use memory and context, and how real-time data can be queried efficiently to power modern application features.

Alongside Redis-focused sessions, we’ll also have additional speakers from the broader tech and AI ecosystem, sharing insights on emerging technologies and real-world implementations.

Agenda:
10:00-10:30 AM - Registration and welcome note
10:30-11:00 AM - MCP + Redis — Build an AI agent that remembers (Live Demo)
Speaker: Rahul Choubey, Senior Solution Architect, Redis
In this session, we'll walk through how to design an AI agent that can remember past interactions and use context effectively. You’ll learn how MCP (Model Context Protocol) helps standardize tool access for AI agents, and how Redis powers key building blocks such as vector search, memory, and caching to reduce latency and cost. The session includes a short end-to-end live demo and a practical architecture pattern you can apply to real-world applications.

What you’ll learn:

• MCP in plain English and why it matters for tool-using agents
• Using Redis for AI workloads: vector search (RAG), memory, and semantic caching
• A simple data model for chunks, metadata, and sessions
• How to avoid repeated and expensive model calls with caching
• A production-ready mental model for agent memory and retrieval

11:00-11:30 AM - Querying real-time data with Redis Query Engine
Speaker: Mohamed Danish Galiyara, Solution Architect, Redis
Redis Query Engine makes it possible to query data stored in Redis using secondary indexes, full-text search, and structured queries — all with real-time performance. This session focuses on how the Redis Query Engine works, the types of queries it supports, and how it can be used to power application features like search, filtering, and real-time views. You’ll gain a clear understanding of when to use the query engine, how to model data for efficient querying, and how to build responsive systems without adding extra infrastructure.

What you’ll learn:

• What the Redis Query Engine is and how it works
• Indexing and querying data stored in Redis
• Running full-text search and structured queries in real time
• Data modeling techniques for efficient querying
• Common use cases such as search, filtering, and real-time views

11:30-02:00 PM - TBD

Who should attend:

• Software engineers and backend developers
• AI engineers and architects
• Developers interested in AI agents, RAG, and real-time systems
• Anyone curious about modern application architecture patterns