LLM-as-Judge

Build a cost-efficient LLM evaluation ensemble for comparing and scoring generative AI outputs at scale.

When to Use

• Evaluating generative AI outputs across multiple models at scale (100+ runs)
• Comparing local/OSS models against cloud baselines in shadow-testing pipelines
• Building promotion gates where models must prove quality before serving production traffic
• Any scenario where deterministic tests alone can't capture output quality

When NOT to Use

• One-off evaluations (just read the output yourself)
• Tasks with deterministic correct answers (use exact-match or unit tests)
• When you can't afford any external API calls (this pattern uses Claude/GPT as judges)

Architecture: Three-Layer Evaluation