◆ LLM-AS-JUDGE EVALUATION PLATFORM

Know if your AI
actually works.

Automated quality evaluation for LLM-powered systems. Detect hallucinations, score faithfulness, measure bias — at scale, without human review.

→ Try the Live Demo See Capabilities
5
Eval Metrics
<2s
Avg Eval Time
0.94
Judge Accuracy
API
Ready

What We Evaluate

Five dimensions of
LLM output quality.

Every metric backed by a research-grounded judge model. Every score explained with evidence.

🔍

Hallucination Detection

Identifies factual claims in the model's output that contradict verifiable knowledge or provided context. Flags specific sentences, not just a score.

CRITICAL SAFETY

Faithfulness Scoring

For RAG systems: measures whether every claim in the response is traceable back to the retrieved context. Catches fabrication even when plausible.

RAG ESSENTIAL
🎯

Answer Relevancy

Scores whether the response actually addresses what was asked. Catches deflection, off-topic responses, and models that answer a different question.

QUALITY CORE
⚖️

Bias Detection

Tests for differential treatment across demographic groups using counterfactual analysis. Surfaces systematic fairness failures invisible to other metrics.

FAIRNESS
📐

Custom Rubric (G-Eval)

Define your own quality criteria in plain language. The judge scores against your rubric — brand voice, legal compliance, domain accuracy, anything you need.

FLEXIBLE

Interactive Demo

See the judge in action.

Select an eval type, load an example, and run the evaluation. All demo data is pre-loaded — no API key needed.

VerdictAI Evaluator ● DEMO MODE
Example Scenario load a preset
Question / Prompt *
Model Response *

Load a scenario and run
the evaluation to see results


How It Works

Three steps to
confident AI quality.

01

Submit your evaluation

Send the question, model response, and optional context via API or web UI. Works with any LLM — GPT, Claude, Gemini, open-source models.

02

Judge evaluates with evidence

A calibrated judge model analyses the response across your chosen metrics, identifying specific claims, gaps, and policy violations with citations.

03

Receive scored verdicts

Get structured scores, pass/warn/fail verdicts, evidence chains, and actionable reasoning — ready to integrate into your CI/CD pipeline.


Who Uses VerdictAI

Built for teams shipping
AI-powered products.

AI/ML QA Engineers

Automate eval coverage at scale

Replace manual review of LLM outputs with automated, research-backed scoring. Integrate into pytest suites, CI pipelines, and release gates.

Product & Engineering Teams

Ship AI features with confidence

Know before you deploy whether your model's output quality meets your bar. Track regressions across model versions with comparable scores.

RAG System Builders

Measure faithfulness end-to-end

Test every link in your retrieval-augmented pipeline — retrieval precision, context coverage, and answer faithfulness — in a single eval run.

Compliance & Safety Teams

Audit AI outputs systematically

Document hallucination rates, bias findings, and safety policy compliance for regulatory review. Every verdict includes an evidence chain.

Start evaluating your
AI outputs today.

No API key needed for the demo. See every metric in action in under 60 seconds.

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