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LLM Evals

Automated tests that score an LLM application output quality (coverage, correctness, tone, safety), typically against a labeled dataset.

What Is LLM Evals?

Common frameworks: DeepEval, Ragas (RAG-specific), Promptfoo, OpenAI Evals, and HumanEval-style custom evals. Each eval runs the LLM against a fixed input set and scores outputs via heuristics, regex, or judge-LLM grading. Critical for catching regressions when you upgrade the model, change the prompt, or update retrieval.

How Groovy Web Uses This

We ship every production AI app with a custom eval suite. Before any prompt or model change goes live, the eval set must pass.

Need Help with This?

Our AI-First engineers build production systems using LLM Evals technology. Talk to us.

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