The Surge AI
Guide to Building World-Class AI Systems
Clear guidance for evaluating, choosing, improving, and deploying AI in real business workflows, written as the questions teams actually ask.
Evaluating AI systems: the fundamentals
Evaluation gives you a structured way to answer practical questions about an AI system: Is it good enough for this workflow? Where does it fail?
Choosing the right evaluation method
Different evaluation methods are suited to different kinds of tasks.
Designing evaluations that actually tell you something
A useful evaluation should help you make a decision, not just produce a score.
Comparing and choosing models
Choosing a model is usually a tradeoff between quality, cost, latency, reliability, and operational requirements.
Improving model performance
Once you understand where a model succeeds and fails, the next question is how to improve it.
Deploying and monitoring AI systems
A model that performs well in an offline evaluation still needs to work reliably inside a real product or workflow.
Kickstart your evaluation program
We work with teams to define evaluation programs around their actual workflows and quality standards.
Talk to our team↗