Qdrant AI Builders: Show & Tell @ AWS Loft
🎉 Join us for an exclusive evening of innovation, networking, and cutting-edge demos at the AWS Loft! 🎉
Qdrant, a vector database for AI and semantic search, is bringing together the brightest minds in vector search, AI, and MLOps for a Show & Tell event designed to inspire and educate. Whether you're an AI engineer, data scientist, researcher, or builder, this is your chance to see real-world applications of vector search in action and connect with a vibrant community of industry experts.
🔥 Expect a curated selection of live demos from companies and individuals who are using Qdrant to build next-generation search, recommendation systems, and AI applications.
🔥 Network with engineers, founders, and investors passionate about the future of AI and machine learning.
🔥 Learn how Qdrant powers Agentic Frameworks, Retrieval-Augmented Generation (RAG), multimodal search, and beyond!
What to Expect
🔹 5:00 PM – Doors Open & Networking 🤝
🔹 5:20 PM – Welcome & Introduction to Qdrant 🎤
🔹 5:40 PM – AWS Presentation 🧑💻
🔹 6:00 PM – Lightning Demos ✨
🔹 8:00 PM Networking
🔹 9:00 PM – Event Ends 🚪
Apply to Demo!
Are you building something exciting with Qdrant? Do you have an innovative application of vector search, AI-powered retrieval, or semantic search?
👩💻 We’re looking for 8-10 incredible demos to feature at this event. Submit your application by TBD to be considered.
Criteria:
✅ Must be an AI/ML application involving search, retrieval, recommendations, discovery, etc.
✅ Must be able to attend the event to present.
✅ Preference for innovative use cases & real-world applications!
Why Attend?
🚀 See cutting-edge AI & search technology in action
🌎 Meet top engineers, researchers, and founders in the AI space
💡 Discover new use cases for Qdrant & vector search
🔗 Connect with the SF AI/ML community in a high-energy, interactive setting
This exclusive, invite-only event is the perfect opportunity to engage with the AI/ML community, exchange insights, and push the boundaries of what's possible with vector search.