Ashwin Hariharan
Developer Advocate @ Redis
Bengaluru, India
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Ashwin Hariharan is a Developer Advocate at Redis, with over eight years of experience as a full-stack software engineer. He's passionate about making complex ideas simple, helping developers build faster, more reliable systems, and understand the "why" behind the tools they use. His current work focuses on applied AI, and exploring how intelligent, real-time applications can be built using retrieval-augmented generation, vector search, agentic AI, and other emerging technologies.
Outside of tech, he spends time learning piano and basic music production, hitting the gym, and exploring big questions about how the world works. He's also fascinated by how people think and learn, often channeling that curiosity into talks, writing, and conversations about science and critical thinking.
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TechNexus Bengaluru - Agentic AI Connect
Title: Architecting Agentic AI Systems with Redis
Summary:
In 1970, Edgar Codd introduced the relational database model, transforming how we store and query data. Before that, programmers had to know exactly where data was stored and how to navigate complex file structures. Codd’s innovation was making data access declarative - you describe what you want, not how to get it.
Today, RAG systems and Agentic AI have made great strides in natural language querying. But there’s still room to make data access even more intuitive and conversational, and responses even more fast and contextual.
This session will cover building intelligent AI agents that can understand natural language queries with intent and context. We’ll explore vector search and semantic caching with Redis, and show how these agents can deliver results at sub milli-second speeds.
Redis Released Delhi
Talk: Context Engineering with Redis: Building AI Agents That Remember and Reuse knowledge
AI workshop: Build a RAG chatbot
Redis powers some of the world’s most responsive and intelligent apps - and now it's your turn to build one.
In this 3 hr workshop, you’ll roll up your sleeves and build a Retrieval-Augmented Generation (RAG) chatbot that’s fast, accurate, and memory-aware - using Redis’ real-time vector search and low-latency data infrastructure.
Key topics:
- How Redis' vector database supercharges GenAI apps
- Real-world architecture for low-latency, memory-rich chatbots
- Step-by-step RAG chatbot build, from ingestion to response
https://www.linkedin.com/posts/iyerashwinhariharan_redis-rag-ai-activity-7388995382913130496-NsGC
Redis Released Bengaluru
Building faster AI Agents through knowledge reuse with LangChain & Redis
AI Agents don’t have to be overthinkers, but if you design them wrong, they’ll happily burn tokens re-answering the same questions. This session will show you how to build AI agents that actually reuse what they already know. You’ll learn:
- Why poor design makes LLMs “overthink” and how to fix it
- How to capture and reuse knowledge with memory and caching
- How to build agents that deliver faster, cheaper, and more consistent results
https://www.linkedin.com/posts/iyerashwinhariharan_redisreleased-activity-7376239213568126978-hDOj
Ashwin Hariharan
Developer Advocate @ Redis
Bengaluru, India
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