This session breaks down what it really takes to build multimodal systems that integrate text, vision, and structured data into one working pipeline. We’ll cover architecture choices, data alignment challenges, and how teams are deploying these models in production. Expect real examples, practical lessons, and the trade-offs no one mentions in the research papers. Key takeaways: → How to structure and align inputs across modalities without breaking your model. → What’s worked (and failed) in real-world deployments of multimodal systems. → When to go unified vs. modular and the engineering trade-offs behind each.