If you’re shipping AI features to users, you’ve likely experienced that inflection point where infrastructure bills start climbing faster than your user growth. It’s a familiar pattern: you launch, users adopt, costs spike, and suddenly you’re trying to optimize spend while maintaining the experience that got users hooked in the first place.
The good news? Running AI in production doesn’t have to mean runaway costs.
We’re hosting office hours on Tuesday, February 3rd from 4-5 PM EST to break down how teams are cutting inference costs by up to 10× without sacrificing latency, quality, or reliability. This isn’t theory, we’ll cover practical strategies that actually work in production environments.
This is an interactive, hands-on session. Come with your current setup, cost challenges, or scaling questions. Whether you’re a founder evaluating your AI stack or an engineer in the trenches optimizing production workloads, this session is designed to give you frameworks and tactics you can apply immediately.
We’ll keep it conversational and focused on real-world trade-offs, the kind of decisions you’re actually making when building AI products.
Register here: https://luma.com/lrvb4dmc
Looking forward to diving into the details with you.
The Neurometric Team