Qdrant AI Builders: Agentic Memory with MCP @ AWS Loft with n8n and Tensorlake
Our CEO, Andre Zayarni, will be joining us in person for this event!
Join us for an exploration of the next frontier in Retrieval-Augmented Generation (RAG): persistent agentic memory and dynamic context injection using MCP (Model Context Protocol) and Qdrant.
We will be joined by n8n and Tensorlake.
As LLM-powered agents become more capable, they need more than just one-off prompts — they need context that evolves, memory that persists, and infrastructure that scales. This event will show you how to use MCP to manage complex, multi-turn contexts, and how Qdrant enables high-performance vector memory at scale.
Through live demos, lightning talks, and hands-on exploration, we’ll walk through how to:
Store long-term memory using Qdrant
Dynamically construct LLM context with MCP
Design agents that remember, adapt, and collaborate across time
Whether you're building copilots, assistants, or AI agents that go beyond single-turn interactions, this event will equip you with the building blocks of intelligent memory.
What You’ll Learn:
How the Model Context Protocol enhances agentic workflows
Architecting scalable vector memory with Qdrant
Best practices for context injection and memory retrieval
Real-world demos of agentic systems powered by MCP and Qdrant
Who Should Attend:
LLM engineers, AI product builders, agent framework devs, and anyone working on context-aware or memory-enabled AI.
This isn’t just RAG — it’s memory with purpose.