Your Inference Bill Is Too High. Here’s How to Fix It.
If you’re running AI in production, you already know the pain: costs that spike with every request, latency that kills user experience, and reliability that degrades under load.
But here’s the thing. For many production tasks, you don’t need a massive frontier model. You need the right model, the right architecture, and the right routing strategy.
We’re bringing together developers, founders, and AI builders in NYC for a hands-on meetup focused on exactly that. Oh, and free snacks.
What we’ll cover:
When to use Small Language Models (SLMs) vs. large models. Not every task needs GPT-5-class reasoning. We’ll break down which production scenarios favor smaller, specialized models and how to identify them in your own stack.
How to design multi-model routing architectures. The real unlock isn’t picking one model. It’s building a system that sends the right query to the right model. We’ll walk through practical routing strategies you can implement today.
Cost, latency & reliability tradeoffs. We’ll look at concrete cases where teams have dramatically cut inference costs by swapping in the right model for the right workload, without sacrificing quality.
Fine-tuning vs. prompting vs. structured outputs. When does each approach pay off? We’ll cover the decision framework we use and how to apply it to your use case.
Building eval pipelines for production reliability. Shipping is one thing. Staying reliable at scale is another. We’ll dig into how to build evals that actually catch regressions before your users do.
This is a hands-on session.
Bring your use cases, your questions, and your production pain points.
Hosted by Neurometric AI Events. See you in New York.
Also, check out our website to access our products.