
Enterprise AI: From Prototype to Production
The gap isn't the model — it's everything around it: agents that can't securely reach real-time business data, data fragmented across transactional systems, war
The gap isn't the model — it's everything around it: agents that can't securely reach real-time business data, data fragmented across transactional systems, warehouses, and vector stores, and architectures that buckle under mixed workloads at scale. Join Microsoft, TiDB, and Dify for an afternoon focused on closing that gap — how to build AI applications on Azure that are scalable, governed, and connected to real business data. What we'll cover Microsoft Foundry — building and governing enterprise AI apps and agents Microsoft Fabric — a unified data platform foundation for AI TiDB — one real-time data layer for transactional, analytical, and vector workloads, so agents stop juggling three databases Dify — shipping AI agents and workflows that plug into real operations You'll walk away with A reference architecture for production AI on Azure A clear case for why production AI needs a unified, real-time data layer — and how to simplify a fragmented AI data stack Agent and workflow implementation patterns you can apply immediately A practical path to modernize existing data infrastructure for AI workloads Who this is for Teams building copilots, agents, or AI-powered applications: AI/GenAI engineers, cloud architects and platform engineers, data engineers and database owners, CTOs and heads of engineering, and digital transformation leaders. If your AI project is stuck between "impressive demo" and "production deployment," this afternoon is for you. Agenda 1:30 PM Registration & welcome 2:00 PM Keynotes: Microsoft · TiDB · Dify 4:00 PM Tea break & networking 4:15 PM Panel: Moving enterprise AI from prototype to production 5:00 PM Tea break & networking 6:00 PM Close Event details Date: Thursday, August 27, 2026 Time: 2:00 PM – 6:00 PM SGT Cost: Free, registration required. Seats are limited — corporate email registrations prioritized.
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