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AI workflows rely on more than a model. They also need current data & 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 & Temporal in New York to explore how durable workflows support AI applications. We'll look at patterns for ingesting & preparing data for RAG, retrieving context, & coordinating agent workflows that can recover after failures.
What we'll explore:
Preparing & indexing data for AI applications with MongoDB Atlas
Coordinating ingestion, retrieval, & agent workflows with Temporal
Designing AI workflows that can recover when steps fail
Who should come:
FinTech Engineers building AI-driven workflows
Developers & 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 & Data
Networking with engineers building production systems for AI & FinTech
Great food, drinks, & real technical conversations
Agenda
6:30 PM - Doors open & check-in
7:00 PM - Introductions & 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, & application state so AI systems can retrieve fresh context & 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.
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