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Vector Space Day SF — Agenda	AGENDA	/img/qdrant-logo.svg	/vsd/vsd-link-preview.jpg	/img/vsd-sf-26/agenda/hero.png	static/img/vsd-sf-26/agenda/	Full agenda for Qdrant Vector Space Day SF 2026 — talks on vector search, AI agents, edge AI, and more at The Midway, San Francisco on June 11th.	Check-in begins at 8:30 AM.<br> First 200 to arrive get exclusive t-shirt.	June 11th, 2026	The Midway, San Francisco	/vector-space-day-sf-26/agenda/	render always	type title speaker_name speaker_role speaker_avatar duration time talk Welcome Adam Chan CEO, HackerSquad /img/vsd-sf-26/agenda/speakers/adam-chan.png 5' 9:30 AM type title description company_logo badge badge_type badge_icon speaker_name speaker_role speaker_avatar duration time talk We Do it the Hard Way Qdrant started for search, and remains for search. From its roots as an open source side project to millions of downloads and thousands of community members worldwide, Qdrant has always sought to build the highest quality search engine, even when that meant doing things the hard way. Hear about our origins, the decisions that shaped the product, and our future trajectory from Qdrant Co-Founder and CEO, Andre Zayarni. Welcome to Vector Space Day. /img/logo-white.png QDRANT qdrant presentation Andre Zayarni CEO, Co-Founder /img/vsd-sf-26/agenda/speakers/andre-zayarni.png 10' 9:35 AM type title description company_logo badge badge_type badge_icon speaker_name speaker_role duration time talk When Search Gets Serious From a strong Rust core to composable retrieval primitives, Qdrant was built from the start for speed, accuracy, and flexibility. Today it supports thousands of projects and a growing number of enterprise businesses around the world, all from the same core engine. But the roadmap is far from finished. Where is Qdrant headed next, and what does it mean for the teams building on it? Come to this session to find out what's coming and why it matters. /img/logo-white.png QDRANT qdrant presentation Manuel Meyer & Neil Kanungo COO & Head of DevRel 15' 9:45 AM type title description company_logo badge badge_type badge_icon speaker_name speaker_role speaker_avatar duration time talk Continual Learning Starts with Memory Continual learning has long been treated as a training problem: new data, new gradients, new weights. But for production agents, the first unlock isn't retraining, it's memory. This talk reframes continual learning as a memory, retrieval, and state-management problem, showing how agents capture interactions, structure durable context, and improve decisions over time. Taranjeet shares patterns from building Mem0, including trade-offs of a memory layer on vector databases and what breaks at scale. /img/vsd-sf-26/vsd-logos/Mem0.svg AGENTS & MEMORY agents brain Taranjeet Singh CEO /img/vsd-sf-26/agenda/speakers/taranjeet-singh.png 20' 10:00 AM type title description company_logo badge badge_type badge_icon speaker_name speaker_role duration time talk Using GraphRAG to Improve Enterprise Governance Enterprise AI agents are only as trustworthy as the rules they operate within. This talk presents a practical blueprint for combining Qdrant's vector search with a Neo4j graph governance layer — building agents that retrieve fast and stay policy-compliant. Through a live demo, we show how the same query returns different results for different users based on governance, not just relevance. Attendees leave with a concrete architecture for enterprise AI agents that are smart, fast, and safe. /img/vsd-sf-26/vsd-logos/Adobe.svg SEARCH & RETRIEVAL search search Murthy Chandrapaty & Ankush Gumber Principal Engineer & Software Engineer 20' 10:20 AM type title duration time break Coffee Break 15' 10:40 AM type title description company_logo badge badge_type badge_icon speaker_name speaker_role speaker_avatar duration time talk Literal Skill Issue: How Skills.md Might Be Holding Your Agents Back SKILLS.md files have saved us from the massive headache of MCP servers, but having a human manually write and update static markdown files just doesn't scale. This session will break down the very real limitations of hardcoding what your agents can do, from brittle maintenance loops to capability ceilings that cap what agents can learn on their own. Come find out why SKILLS.md is just our awkward transitional phase, and how we're going to replace it with dynamic, autonomous tooling that evolves as your agents do. /img/vsd-sf-26/vsd-logos/Google-Deepmind.svg AGENTS & MEMORY agents brain Paige Bailey Developer Relations Lead /img/vsd-sf-26/agenda/speakers/paige-bailey.png 20' 10:55 AM type title description company_logo badge badge_type badge_icon speaker_name speaker_role speaker_avatar duration time talk Free Your Agent's Mind...with Context Graphs AI systems need more than intelligence; they need context that persists. Without it, even strong models misinterpret information, lose decision rationale, or repeat mistakes. Context Graphs address this: a living graph capturing not just what was retrieved, but how context led to actions through tool calls, constraints, and outcomes, stitched across entities and time. This talk shows how context graphs complement retrieval with multi-hop structured assembly and built-in provenance for enterprise-ready AI. /img/vsd-sf-26/vsd-logos/Neo4j.svg AGENTS & MEMORY agents brain Stephen Chin VP of DevRel /img/vsd-sf-26/agenda/speakers/stephen-chin.png 20' 11:15 AM type title description company_logo badge badge_type badge_icon speaker_name speaker_role duration time talk Building the Infra Behind 20 Billion+ Vectors This talk traces HubSpot's journey from a Helm-based Qdrant deployment, where cluster provisioning and scaling were manual, error-prone, multi-step processes, to a fully automated Kubernetes Operator built on HubSpot's internal kube-operators framework. Learn how the team designed the operator to handle rolling upgrades, automated scaling, and self-healing across a fleet managing 20 billion+ vectors, and the lessons learned running Qdrant at this scale in production. /img/vsd-sf-26/vsd-logos/Hubspot.svg SEARCH & RETRIEVAL search search Oleg Tereshin & Xin Liu Sr SWE II & Tech Lead 20' 11:35 AM type title description company_logo badge badge_type badge_icon speaker_name speaker_role duration time talk Scaling to Billions: Lessons from Slack's Semantic Search Indexing Slack's semantic search indexes trillions of messages into vectors, kept searchable within seconds. This open discussion skips the "perfect world" diagrams and covers what it actually takes to run a vector pipeline at this scale: a Lambda architecture with a "snowball" caching system to avoid recomputing billions of embeddings weekly, greedy batching for a 3x inference speedup, and a candid look at why complex quantization methods failed in production. /img/vsd-sf-26/vsd-logos/Slack.svg SEARCH & RETRIEVAL search search Avirek Ghatia & Brian O'Grady Staff Software Engineer at Slack & Head of Solutions Architecture at Qdrant 20' 11:55 AM type title duration time break House Keeping 5' 12:15 PM type title duration time break Lunch Break 60' 12:20 PM type title description company_logo company_logo_offset badge badge_type badge_icon speaker_name duration time talk Building the DNA of Search Qdrant was engineered from the ground up for performance, scale, and flexibility — and Oncotelic Therapeutics put it to the test. Indexing 28M PubMed abstracts to power AI-driven drug development, Oncotelic compressed concept-to-clinic to ~2 years — a fraction of the typical biotech timeline. In this conversation, Qdrant Engineering and Oncotelic walk through what matters most for search at scale: hybrid retrieval, MeSH-enriched metadata filtering, and the operational realities of running a vector database in production. /img/vsd-sf-26/vsd-logos/qdrant+oncotelic.svg placement value top -8 QDRANT qdrant presentation Bastian Hofmann, Head of Product at Qdrant & Saran Saund, CBO at Oncotelic Therapeutics & Scott Myers, PM at Oncotelic Therapeutics 20' 1:20 PM type title description company_logo badge badge_type badge_icon speaker_name speaker_role speaker_avatar duration time talk Building Distributed, Enterprise-ready Agentic AI A high-level look at building intelligent, enterprise-grade AI agents using modern tools and infrastructure. This session explores how scalable systems can support context-aware reasoning, long-term memory, and real-time decision-making at production scale. We frame the key architectural patterns behind reliable AI agents in enterprise environments, from retrieval and orchestration to evaluation and observability. Learn how Vultr's global cloud infrastructure powers distributed AI workloads for companies shipping agents today. /img/vsd-sf-26/vsd-logos/Vultr.svg AGENTS & MEMORY agents brain Gabriel Lebow Sr GPU Solutions Engineer /img/vsd-sf-26/agenda/speakers/gabriel-lebow.png 20' 1:40 PM type title description company_logo badge badge_type badge_icon speaker_name speaker_role speaker_avatar duration time talk The Document Harness: What Your AI Misses in the 90% An estimated 90% of enterprise data is unstructured, living in PDFs, PowerPoints, Word, and Excel files that power a majority of knowledge work. There's a huge opportunity to build autonomous agents that can understand, reason over, and edit massive quantities of documents. But real-world documents are too complex for even frontier models to understand. This session walks through core challenges and advances in document OCR and agent harnesses enabling modern document workflow automation. /img/vsd-sf-26/vsd-logos/LlamaIndex-white.svg AGENTS & MEMORY agents brain Preston Carlson AI Engineer /img/vsd-sf-26/agenda/speakers/preston-carlson.png 20' 2:00 PM type title description company_logo badge badge_type badge_icon speaker_name speaker_role speaker_avatar duration time talk Stop Vibe Shipping: Evaluate Your Retrieval "Looks good to me" is not an evaluation strategy. Yet most teams ship retrieval systems that way: tweak the chunking, run a few demo queries, call it done. This talk replaces vibes with measurement. We'll cover retrieval metrics that actually matter, how to build golden datasets that survive contact with reality, where LLM-as-judge helps and where it lies, and how to wire continuous evals into CI so regressions show up before customer complaints. /img/vsd-sf-26/vsd-logos/ArizeAI.svg SEARCH & RETRIEVAL search search Laurie Voss Head of DevRel /img/vsd-sf-26/agenda/speakers/laurie-voss.png 20' 2:20 PM type title description company_logo badge badge_type badge_icon speaker_name speaker_role speaker_avatar duration time talk Beyond the Single API Call: Agentic Video Intelligence Video is a highly information-dense modality, and processing it at scale requires more than standard embed-store-retrieve pipelines. This talk explores how Twelve Labs' multimodal foundation models enable rich semantic understanding of video, from domain-specific search to structured metadata extraction. We'll walk through a real-world anomaly detection app built on Twelve Labs and Qdrant, and introduce Jockey, an agentic framework for multi-step video workflows. /img/vsd-sf-26/vsd-logos/TwelveLabs.svg SEARCH & RETRIEVAL search search James Le Head of Dev Experience /img/vsd-sf-26/agenda/speakers/james-le.png 20' 2:40 PM type title duration time break Coffee Break 15' 3:00 PM type title description company_logo badge badge_type badge_icon speaker_name speaker_role speaker_avatar duration time talk The Long and the Short of AI Memory What is AI Memory today? Where does it live: markdown files, vectors, graphs, or somewhere else? And where will it be tomorrow? The answer matters because memory is quickly becoming the differentiator between agents that forget everything between sessions and agents that actually compound knowledge over time. In this talk, Dave will share examples of how short-term and long-term memory are used in production today, using OpenClaw as a hands-on example to illustrate the patterns and trade-offs. /img/vsd-sf-26/vsd-logos/Cognee.svg AGENTS & MEMORY agents brain Dave Nielsen Head of DevRel /img/vsd-sf-26/agenda/speakers/dave-nielsen.png 20' 3:15 PM type title description company_logo badge badge_type badge_icon speaker_name speaker_role speaker_avatar duration time talk The World is Becoming More Searchable The surface areas of search are only increasing as more and more data is captured from the physical and digital world. Embeddable systems unlock the ability to run local search across millions of devices, enabling AI at the edge without relying on round trips to the cloud. Come to this session to hear about Qdrant Edge: what it is, how it's built, the use cases it opens up, and why we think it fundamentally changes the game for teams building on-device AI experiences. /img/logo-white.png EDGE & ROBOTICS edge database Dylan Couzon DevRel Engineer /img/vsd-sf-26/agenda/speakers/dylan-couzon.png 20' 3:35 PM type title description company_logo badge badge_type badge_icon speaker_name speaker_role speaker_avatar duration time talk When Latency Is the Product: Practical Patterns for On-Device GenAI Agents are moving from the cloud to the edge - onto phones, PCs, and edge devices that perceive and act in real time. I'll share practical patterns for building agentic AI on-device: how to run models and tap local context for retrieval and memory. This runs on the NPU - a chip built for AI inference. That's why sustained, private, low-latency AI workloads win on the edge. And Qualcomm AI Hub is how you ship it: optimize any model and run it across devices. /img/vsd-sf-26/vsd-logos/Qualcomm.svg EDGE & ROBOTICS edge database Alan Zhu DevRel Engineer /img/vsd-sf-26/agenda/speakers/alan-zhu.png 20' 3:55 PM type title description company_logo badge badge_type badge_icon speaker_name speaker_role speaker_avatar duration time talk Tell the Robot What You Want Learn how to build robots that respond to natural language commands using an open-source agentic AI framework. Sensors and actuators become agent tools, translating intents into actions. A lightweight hybrid architecture handles low-latency control locally on edge devices while delegating complex reasoning to the cloud. Explore hybrid edge-cloud patterns for low-latency control and intelligent planning, demonstrated live with a working robot. /img/vsd-sf-26/vsd-logos/AWS.svg EDGE & ROBOTICS edge database Sandhya Subramani Sr. Dev Advocate, GenAI /img/vsd-sf-26/agenda/speakers/sandhya-subramani.png 20' 4:15 PM type title duration time break Closing Remarks & Hackathon Winners 25' 4:35 PM type title time break Happy Hour 🎉 5:00 PM