Your AI
judges itself.
Autonomously.

LLM-as-a-judge evaluation API. Send a prompt, response, and criteria — get back a structured quality score with reasoning. Every eval stored for trend analysis.

Try the Live Demo ↓
eval://production — live
coherence
gpt-4o-mini
4.7
factual_accuracy
claude-3.5-sonnet
4.2
instruction_following
gemini-2.0-flash
4.8
safety_alignment
llama-4-scout
3.1
1-5 scale · LLM-as-judge 765 evals

Live Demo

Run a real evaluation against the API. Scores 1-5 with structured reasoning.

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Evaluation Complete

Every prompt change is a dice roll. Every model update, a leap of faith.

Silent regressions

A model update ships Tuesday. Thursday, your chatbot starts hallucinating. You find out Monday from a customer complaint.

Manual eval pipelines

Your team spends 20+ hours a week writing test cases, running evaluations, comparing results. Time that should go to building product.

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Wrong metrics

Generic benchmarks tell you nothing about your use case. MMLU scores don't predict whether your support agent handles refunds correctly.

API Quick Start

# Evaluate an LLM response curl -X POST https://gauge-jiez.polsia.app/api/evaluate \ -H "Content-Type: application/json" \ -d '{ "prompt": "Explain quantum computing", "response": "Quantum computing uses qubits...", "criteria": "Clear, accurate, accessible" }' # Response { "success": true, "evaluation": { "score": 4, "reasoning": "Clear explanation with good analogies...", "criteria_met": ["Clear", "Accessible"], "criteria_missed": ["Could be more detailed"], "model": "gpt-4o-mini", "eval_duration_ms": 1240 } }

LLM-as-Judge

Structured 1-5 scoring using frontier models. JSON output with reasoning, criteria met, and criteria missed.

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History & Analytics

Every evaluation stored. Track quality over time. Get score distributions and trend data via the stats API.

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Custom Criteria

Define your own evaluation dimensions — accuracy, tone, completeness, safety. Score what matters to your product.

Fast & Lightweight

Simple REST API. No SDKs to install, no agents to configure. One POST request, one structured result.