Durable AI Workflows with Temporal and MongoDB

AI workflows rely on more than a model. They also need current data and a way to recover when a model, API, or other step fails. In financial services, where a repeated payment or a dropped step has real consequences, that recovery story matters even more. Join MongoDB and Temporal in New York to explore how durable workflows support AI applications. We’ll look at patterns for ingesting and preparing data for RAG, retrieving context, and coordinating agent workflows that can recover after failures. What we’ll explore: Preparing and indexing data for AI applications with MongoDB Atlas Coordinating ingestion, retrieval, and agent workflows with Temporal Designing AI workflows that can recover when steps fail Who should come: FinTech Engineers building AI-driven workflows Developers and architects building AI or data-intensive applications Engineers exploring RAG, agents, or vector search Teams interested in making multi-step AI workflows more dependable What's Happening: 🎤 Talks & demos from engineers working in AI and Data 🤝 Networking with engineers building production systems for AI and FinTech 🥘 Great food, drinks, and real technical conversations Agenda 6:30 PM - Doors open and check-in 7:00 PM - Introductions and welcome 7:10 PM - First Round of talks (TBD) 7:40 PM - Break 7:50 PM - Second Round of talks (TBD) 8:20 PM - Closing 8:30 PM - Event close About MongoDB MongoDB is a developer data platform for building modern applications. MongoDB Atlas unifies operational data, vector search, and application state so AI systems can retrieve fresh context and act on it in real time. About Temporal Temporal is a durable execution platform for crash-proof code. Whether it's an AI agent or a bank money transfer, your application is guaranteed to execute to completion in the face of failure.