LLM Evaluation & QA Services | Expert Human Testers | JudgeMyAI
SERVICE // EVALUATION & QA

LLM Evaluation &
Quality Assurance

Don't guess if your model is aligned. Know it. We provide the expert human intelligence required to evaluate, grade, and perfect Large Language Model outputs at scale.

Live QA Rubric
Prompt Context
Acc.
Safe.
Flu.
Medical Diagnosis Query
98%
100%
95%
Code Refactor Request
74%
100%
90%
Adversarial Injection
12%
0%
85%
Legal Summary Task
99%
100%
98%
CORE COMPETENCIES

What is LLM Evaluation & QA?

Comprehensive human-in-the-loop solutions for artificial intelligence alignment and quality control.

  • LLM Evaluation Rigorous human assessment of Large Language Models to ensure response quality, accuracy, and alignment with human intent. Evaluators grade outputs on instruction-following, coherence, and helpfulness.
  • QA (Quality Assurance) Systematic testing and validation of AI outputs to maintain high standards across various tasks and domains. This includes edge-case testing, tone verification, and safety checks.
  • Fact-Checking & Grounding Expert verification of AI-generated text against trusted sources to identify and eliminate hallucinations, ensuring models are grounded in factual reality.
  • Preference Ranking (RLHF) Generating high-quality preference data by ranking multiple model outputs, enabling Reinforcement Learning from Human Feedback for fine-tuning reward models.
EVALUATION METRICS

How We Grade Models

Every output is measured against a multi-dimensional rubric tailored to your specific use case.

Instruction Adherence

Does the model follow constraints? We evaluate formatting, length, tone, and strict adherence to system prompts and user constraints.

Factual Accuracy

Is the output true? Domain experts verify claims, citations, and data points against ground truth to eliminate subtle hallucinations.

Safety & Toxicity

Is it safe? We test for bias, PII leakage, harmful instructions, and toxic content to ensure enterprise-ready safety guardrails.

Coherence & Fluency

Does it sound natural? Linguists grade grammar, flow, context retention, and overall readability to ensure human-like communication.

THE PROTOCOL

The QA Pipeline

PHASE 01

Rubric Architecture

We collaborate with your team to design a custom evaluation rubric. We define what "good" looks like for your specific domain, establishing strict pass/fail criteria for accuracy, tone, and safety.

PHASE 02

Prompt Generation & Edge Cases

Our experts craft adversarial and edge-case prompts designed to break the model. We test the boundaries of the LLM to find vulnerabilities before deployment.

PHASE 03

Expert Human Grading

Vetted domain experts (PhDs, engineers, linguists) grade the model's responses. They don't just click buttons; they provide qualitative feedback and corrections for every failed metric.

PHASE 04

Preference Data Delivery

We deliver high-fidelity datasets ready for SFT (Supervised Fine-Tuning) and RLHF (Reinforcement Learning from Human Feedback), closing the loop on your model iteration cycle.

IMPACT

The JudgeMyAI Effect

Stop relying on automated metrics that miss the nuance. See the difference expert human QA makes.

Standard Model Output
  • High hallucination rates on niche topics
  • Fails complex multi-step reasoning
  • Inconsistent formatting and tone
  • Vulnerable to prompt injection
  • Automated metrics pass, humans reject
Post-JudgeMyAI QA
  • 94% reduction in factual hallucinations
  • Flawless execution of edge-case logic
  • Strict adherence to brand voice guidelines
  • Robust safety guardrails under stress
  • High-fidelity RLHF preference data generated
INTEL

QA & Evaluation FAQs

What is LLM Evaluation and QA?
LLM Evaluation and QA (Quality Assurance) is the process of using expert human intelligence to assess Large Language Model outputs. It ensures responses are accurate, aligned with human intent, factually grounded, and free from harmful content or hallucinations.
How fast can you deploy a custom LLM evaluation team?
We can deploy a custom, domain-specific evaluation team within 48 hours. We maintain a pre-vetted bench of 3,200+ specialists across 14 domains, including coding, law, medicine, and creative writing.
What makes your evaluators different from generic data labeling platforms?
Our evaluators pass a 4-stage vetting protocol with a 2% acceptance rate. They are domain experts — PhDs, published researchers, former engineers — not generic crowd workers, ensuring high-fidelity RLHF and QA data.
Do you support multi-lingual LLM evaluation?
Yes. We support LLM evaluation in 47 languages with native-level fluency requirements to ensure cultural and semantic nuance is accurately captured.
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your model?

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