Build vs. Buy: AI Infra Options for Production-Ready AI

How do fast-moving AI teams deliver cutting-edge performance without drowning in infrastructure?

In this session, SwingVision, makers of the #1 AI tennis and pickleball app, joins Encord to share how they’ve built a real-time computer vision system that runs on-device, at scale!

We’ll unpack the key decisions that helped them accelerate ML development, manage complex edge cases, and avoid building costly tooling from scratch.


What You’ll Learn:

• How SwingVision structures their AI data stack for speed, trust, and scale
• Frameworks for deciding when to build in-house vs. integrate external tools
• How they identify and retrain on high-impact edge cases
• Where tools like Encord help reduce technical debt and unlock model velocity

If you're leading AI infrastructure or ML teams, this conversation will help you rethink how to prioritize engineering time, increase iteration speed, and scale smarter.