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+---
+title: Judge Builder
+description: Build, test, and deploy custom LLM judges directly from the MLflow UI. Define evaluation criteria with natural language, preview results on real traces, and schedule automatic evaluation—no code required.
+date: 2026-01-23
+authors:
+  - name: MLflow Team
+---
+
+# Judge Builder
+
+![Judge Builder Hero](./hero.png)
+
+## What's New
+
+MLflow 3.9 introduces the **Judge Builder**, a visual interface for creating custom LLM judges directly in the MLflow UI.
+
+Evaluating LLM applications is challenging because quality is often subjective and context-dependent. While MLflow has long supported LLM-as-a-Judge evaluation through the SDK, creating and iterating on judges required coding expertise and constant context-switching between your IDE and the traces UI. With Judge Builder you can now define evaluation criteria using natural language, and test judges on real traces directly from the UI.
+
+## Get Started
+
+```bash
+pip install 'mlflow[genai]>=3.9'
+mlflow server
+```
+
+### 1. Navigate to the Judges Tab
+
+From any experiment in MLflow, select the **Judges** tab and click **New LLM judge** to open Judge Builder.
+
+### 2. Define Your Evaluation Scope
+
+Choose what you want to evaluate:
+
+- **Traces**: Evaluate individual request-response pairs for quality, correctness, and safety
+- **Sessions**: Evaluate entire multi-turn conversations for coherence and goal completion
+
+### 3. Configure Your Judge
+
+The Judge Builder provides an intuitive interface for defining your judge:
+
+| Field            | Description                                                                                                                      |
+| ---------------- | -------------------------------------------------------------------------------------------------------------------------------- |
+| **LLM Judge**    | Start from a built-in judge or select "Custom judge" for full control                                                            |
+| **Name**         | A unique identifier for your judge (e.g., `tone_checker`, `accuracy_evaluator`)                                                  |
+| **Instructions** | Natural language criteria using template variables like `{{ inputs }}`, `{{ outputs }}`, `{{ trace }}`, and `{{ conversation }}` |
+| **Output Type**  | The return type: boolean, categorical, numeric, or structured                                                                    |
+| **Model**        | Select an AI Gateway endpoint or specify a model directly                                                                        |
+
+### 4. Test on Real Data
+
+Before saving, click the trace/session selector to choose specific traces or sessions and click **Run judge** to preview evaluation results. This lets you validate that your instructions produce the expected assessments.
+
+See the [Judge Builder documentation](/genai/eval-monitor/scorers/llm-judge/judge-builder) for more details.